Directorio de IA

Claude Haiku 4.5

Anthropic

Recomendado

La referencia de valor de Anthropic a $1/$5 por 1M de tokens — el nivel rápido y de bajo costo contra el que se comparan los rivales, con contexto de 200K y salida de 64K. Ideal para trabajo de alto volumen sensible a la latencia: clasificación, extracción, resúmenes y enrutamiento. Conviene recurrir a Opus 4.8 o Sonnet 5 cuando se necesita razonamiento profundo de múltiples pasos.

Entrada

$1 / 1M tokens

Salida

$5 / 1M tokens

Contexto

200K ctx; legacy, Haiku 5.5 is current

Claude Opus 4.8

Anthropic

Recomendado

Claude Opus 4.8 is Anthropic's previous-generation Opus, now listed as legacy: 1M-token context, 128K output, $5/$25 per 1M tokens, retirement not before 28 May 2027. It remains our pick for review-heavy work such as code review and constrained refactoring, where deliberate pacing beats persistence. New workloads should start on Claude Opus 5.5 at $4/$20, which Anthropic now recommends.

Entrada

$5 / 1M tokens

Salida

$25 / 1M tokens

Contexto

1M tokens

Claude Opus 5

Anthropic

Recomendado

Claude Opus 5 delivers near-Fable 5 intelligence at $5/$25 per 1M tokens, with a 1M-token context and 128K output. Anthropic now lists it as legacy: still available, retirement not before 24 July 2027, and Claude Opus 5.5 ($4/$20) is its recommended starting point. Recommended for teams already running Opus 5; new workloads should start on Opus 5.5, which is cheaper per token.

Entrada

$5.00 / 1M tokens

Salida

$25.00 / 1M tokens

Contexto

1M ctx; 128K out; legacy; fast $10/$50

Claude Sonnet 5

Anthropic

Recomendado

Anthropic's most agentic Sonnet at launch delivers performance close to Opus 4.8 at 40 percent of the Opus rate. The $2/$10 per 1M token price is the standard rate: Anthropic cancelled the increase to $3/$15 that was scheduled for 1 September 2026. The newer tokenizer produces about 30 percent more tokens for the same text, so recount budgets before migrating from Sonnet 4.6. Anthropic now lists Sonnet 5 as legacy; Claude Sonnet 5.5, at the same $2/$10, is the current Sonnet, so start new work there.

Entrada

$2 / 1M

Salida

$10 / 1M

Contexto

1M tokens; batch $1/$5; cache read $0.20

DeepSeek V4 Flash

DeepSeek

Recomendado

DeepSeek retired V4 Flash from its API on 10 September 2026: the deepseek-v4-flash id is still accepted, but its requests are served by V4.1-Flash and billed at the Flash rate of $0.15 input and $0.60 output per 1M tokens off-peak. The MIT-licensed weights (284B parameters, 13B active, 1M-token context) remain on Hugging Face, so this is now a frozen checkpoint for self-hosting and reproducible evals. For new API work, call deepseek-flash.

Entrada

$0.15 / 1M tokens

Salida

$0.60 / 1M tokens

Contexto

Retired Sep 10; id serves V4.1-Flash. Peak 2x M-F

DeepSeek V4 Pro

DeepSeek

Recomendado

Strong price-performance on open MIT weights; the 2x peak window is 01:00-04:00 and 06:00-10:00 UTC on weekdays only, so weekends bill entirely off-peak.

Entrada

$0.66 / 1M tokens

Salida

$1.98 / 1M tokens

Contexto

1M tokens; 2x price at weekday peak hours

Gemini 2.5 Pro

Google

Recomendado

Ahora la opción económica para contexto largo: un recorte del 40% en precios (jun 2026) hizo que procesar corpus completos sea accesible para presupuestos medios. Ofrece la ventana de contexto más larga disponible, con fuerte integración en el ecosistema de Google.

Entrada

$1.25 / 1M tokens

Salida

$10 / 1M tokens

Contexto

1M tokens

Gemini 3.5 Flash

Google

Recomendado

El destacado de Google en eficiencia de costos para la automatización agéntica de escritorio a $1.50/$9 por 1M de tokens con contexto de ~1M. Su Computer Use nativo obtiene 78.4 en OSWorld-Verified — a 0.3 puntos de GPT-5.5 a aproximadamente un tercio del costo. LA salvedad relevante: la herramienta Computer Use es una vista previa pública que aún no está en la API de producción, así que conviene verificar la disponibilidad del endpoint antes de integrarla.

Entrada

$1.50 / 1M tokens

Salida

$9 / 1M tokens

Contexto

1M tokens

Gemini 3.5 Flash-Lite

Google

Recomendado

Gemini 3.5 Flash-Lite es el modelo más rápido y barato de la serie 3.5 de Google, a 350 tok/s y $0,30/$2,50. El salto generacional desde 3.1 Flash-Lite es la verdadera historia — supera con creces a su predecesor en benchmarks agénticos clave y vence al Gemini 3 Flash completo en tareas de programación y uso del ordenador. Para desarrolladores que escalan subagentes agénticos de alto rendimiento, pipelines de búsqueda y procesamiento de documentos, la relación precio-rendimiento de Flash-Lite no tiene rival en la gama de Google.

Entrada

$0.30 / 1M

Salida

$2.50 / 1M

Contexto

1M context, 64K output, 350 tok/s

Gemini 3.6 Flash

Google

Recomendado

Gemini 3.6 Flash is Google's new default Flash-tier workhorse: better than 3.5 Flash on every benchmark and cheaper, at $0.75/$3.75 per 1M tokens through 2026-12-31, rising to $1.50/$7.50 from 2027-01-01. The 17% token-efficiency gain lowers per-task cost, and built-in Computer Use via the API makes it a credible agentic coding option. For Google-ecosystem developers it is the clear upgrade; budget for the January rate step.

Entrada

$0.75 / 1M (through 2026-12-31)

Salida

$3.75 / 1M (through 2026-12-31)

Contexto

1M context, 64K output; $1.50/$7.50 from 2027-01-01

Gemini 3.7 Flash

Google

Recomendado

Gemini 3.7 Flash es el caballo de batalla Flash más potente de Google hasta la fecha para codificación y agentes: una mejora real frente a 3.6 Flash, a la mitad del precio anterior durante 2026. Sigue por detrás de la frontera en las tareas más difíciles de terminal y uso de computadora. Una actualización clara para quienes construyen agentes sensibles al costo y dentro del ecosistema de Google; no es un reemplazo de la codificación de frontera.

Entrada

$0.75 / 1M

Salida

$3.75 / 1M

Contexto

1M context, 64K output

Gemini 3.8 Flash

Google

Recomendado

Gemini 3.8 Flash is Google's strongest Flash workhorse yet — a genuine capability upgrade over the recommended 3.7 Flash at the same introductory price, with real gains across software engineering, agents and professional domains. The deciding caveat is Google's own: 3.8 "works harder," so per-task token burn runs well above 3.7, which remains the efficiency-first pick. Adopt 3.8 for long-horizon coding, agents and finance or legal work — benchmark your own workload before the intro price expires.

Entrada

$0.75 / 1M

Salida

$3.75 / 1M

Contexto

1M context, 64K output

Gemini 3.8 Live Extended Thinking

Google

Recomendado

Gemini 3.8 Live Extended Thinking is the voice-agent model to start with: it tops Artificial Analysis' Speech to Speech Index and reasons and calls tools in the background while it keeps talking, at the same rate as the default Gemini 3.8 Live. The caveat is the Live API surface: no structured outputs, caching, code execution or batch. Right for teams building real-time voice agents that must solve multi-step problems mid-call.

Entrada

$0.75 / 1M (text)

Salida

$4.50 / 1M (text)

Contexto

131K in, 65K out; audio $3/$12 per 1M

GPT-4.1

OpenAI

Recomendado

El destino de migración por defecto para cargas de trabajo de GPT-4 Turbo: misma estructura de solicitudes, menor costo, contexto de 1M tokens — convierte los payloads heredados de function_call al formato tools y sigue adelante.

Entrada

$2 / 1M tokens

Salida

$8 / 1M tokens

Contexto

1M tokens

GPT-5.5

OpenAI

Recomendado

GPT-5.5 is OpenAI's April 2026 general-purpose model at $5 input and $30 output per 1M tokens, with a 1M+ token context (922K in, 128K out). It is no longer OpenAI's only deployable frontier option: the GPT-5.6 family is on the public price list, and GPT-6 Sol lists at $2/$10. It stays recommended as a stable, widely supported production baseline, but new workloads should test GPT-6 Sol or GPT-5.6 Terra first.

Entrada

$5 / 1M tokens

Salida

$30 / 1M tokens

Contexto

1M+ tokens (922K in / 128K out)

GPT-5.6 Sol

OpenAI

Recomendado

GPT-5.6 Sol is no longer OpenAI's best-value frontier model: its successor GPT-6 Sol, released 22 September 2026, lists at $2/$10 per 1M tokens against Sol's $4/$20. It stays recommended because its coding lead has third-party backing, while every GPT-6 Sol score so far is OpenAI's own. OpenAI lists no deprecation, and the $4/$20 rate is promotional through at least 21 November 2026. Test GPT-6 Sol before committing new workloads.

Entrada

$4 / 1M tokens

Salida

$20 / 1M tokens

Contexto

Short $4/$20 · long $8/$30 per 1M · promo

GPT-Live-Transcribe

OpenAI

Recomendado

El modelo de voz a texto en streaming de baja latencia de OpenAI entrega deltas de transcripción en vivo a $0.017/min con latencia ajustable y transcripción consciente del contexto. Mejora la tasa de error de gpt-realtime-whisper y soporta sugerencias de palabras clave en tiempo real, sugerencias de idioma y actualizaciones de configuración a mitad de sesión vía WebSocket o WebRTC. El compromiso: ~3.8× el coste de GPT-Transcribe por lotes, y sin diarización, marcas de tiempo de palabras ni puntuaciones de confianza. Ideal para subtitulado en vivo, asistentes de reuniones y agentes de voz donde la visualización de transcripción en menos de un segundo importa más que el coste por minuto.

Entrada

$0.017 / minute

Salida

N/A

Contexto

Per-minute realtime audio billing

GPT-Transcribe

OpenAI

Recomendado

El último modelo de speech-to-text por lotes de OpenAI alcanza un 3.31% AA-WER a $0.0045/min — un 25% más barato y mediblemente más preciso que su predecesor gpt-4o-transcribe. Soporta indicaciones de contexto, sugerencias de palabras clave y detección de idioma en más de 22 idiomas, lo que lo convierte en la mejor opción predeterminada para transcripción asíncrona de archivos en la plataforma OpenAI. Limitación: sin diarización ni marcas de tiempo a nivel de palabra; usa gpt-4o-transcribe-diarize para etiquetas de hablante o gpt-live-transcribe para necesidades en tiempo real. Ideal para desarrolladores que construyen transcripción de reuniones, procesamiento de medios e interfaces de voz sobre la API de OpenAI.

Entrada

$0.0045 / minute

Salida

N/A

Contexto

Per-minute audio billing

Claude Fable 5

Anthropic

Condicional

Anthropic's Mythos-class frontier model, the strongest publicly available Claude at its June 2026 launch, now listed as legacy behind Claude Fable 5.1. The verdict stays conditional on two constraints: API pricing of $10/$50 per 1M tokens, and a safety classifier that over-triggered on routine coding tasks at launch, routing them to an Opus 4.8 fallback. Subscribers reach Fable through Claude Max at 50% of weekly limits, or through usage credits on Pro. Anthropic's current lineup lists Fable 5.1 and Opus 5.5 for new work.

Entrada

$10 / 1M tokens

Salida

$50 / 1M tokens

Contexto

1M ctx, 128K out; legacy; Max plans at 50% limits

Claude Fable 5.1

Anthropic

Condicional

Anthropic's new frontier flagship is the most capable model publicly available, and it largely fixes the safeguard over-triggering that made Fable 5 frustrating for routine coding. The verdict stays conditional on cost: independent measurement shows more spend per task than Fable 5 despite the cheaper cache reads, because the model thinks longer. Reach for it on demanding reasoning and long-horizon agentic work. For everyday coding, Claude Opus 5.5 at $4/$20 per 1M is Anthropic's recommended starting model and the better default.

Entrada

$10 / 1M tokens

Salida

$50 / 1M tokens

Contexto

1M context, 128K output; cache $0.25/1M

Claude Haiku 5.5

Anthropic

Condicional

Claude Haiku 5.5 is a conditional pick: Anthropic's fastest and cheapest current Claude at $0.10 input and $0.50 output per 1M tokens, with a 1M context and adjustable effort. Prompts over 100K tokens cost five times as much, and every benchmark is Anthropic's own. Right for high-volume classification, extraction, routing and subagent work. Use Sonnet 5.5 for complex agentic coding, where Anthropic's own Terminal-Bench 4.0 numbers put it well ahead.

Entrada

$0.10 / 1M tokens

Salida

$0.50 / 1M tokens

Contexto

1M ctx; prompts over 100K cost $0.50/$2.50

Claude Mythos 5.1

Anthropic

Condicional

Same weights as Claude Fable 5.1 at the same $10/$50 rate, with cyber and life-sciences safeguards loosened for vetted users. The catch is access: Mythos 5.1 ships only through Anthropic's trusted-access programs (Cyber Verification and Life Sciences Verification), so there is no self-serve API and no way to buy your way in. Conditional for the same reason as Mythos 5: elite capability behind a vetting gate. Everyone else should use Fable 5.1.

Entrada

$10 / 1M tokens

Salida

$50 / 1M tokens

Contexto

1M context, $0.25/1M cache; vetted access

Claude Opus 5.5

Anthropic

Condicional

Claude Opus 5.5 is the model Anthropic now recommends starting with for most workloads, built for long-running agentic coding and knowledge work at rates 20% below Claude Opus 5. Conditional because every benchmark is Anthropic's own and migration is not drop-in: thinking cannot be turned off, forced tool use returns an error, and most cybersecurity tasks are rerouted to Opus 4.8. Right for Claude Opus 5 teams that can absorb those breaking changes.

Entrada

$4 / 1M tokens

Salida

$20 / 1M tokens

Contexto

1M ctx; 128K out; cache $0.20; fast $8/$40

Claude Sonnet 4.6

Anthropic

Condicional

Superseded by Claude Sonnet 5 (shipped Jun 30, 2026), which Anthropic now lists as legacy behind Claude Sonnet 5.5 as the current Sonnet. Both list at $2/$10 per 1M tokens against Sonnet 4.6's $3/$15, since Anthropic cancelled the scheduled rise to $3/$15. Sonnet 5 also adds a 13.4-point Terminal-Bench 2.1 jump. Choose 4.6 only for pinned deployments or where Sonnet 5's ~30% higher token count and removed temperature/top_p/top_k are disqualifying.

Entrada

$3 / 1M tokens

Salida

$15 / 1M tokens

Contexto

1M tokens

Claude Sonnet 5.5

Anthropic

Condicional

Conditional. Claude Sonnet 5.5 is Anthropic's default Sonnet model on the Anthropic API, on the same rate card as Sonnet 5, and Anthropic says it runs faster and costs less per task. Every benchmark is Anthropic's own, and five breaking changes hit code written for Sonnet 5. Right for teams ready to re-test agentic coding and knowledge work; hold off if you rely on forced tool choice or temperature control.

Entrada

$2 / 1M tokens

Salida

$10 / 1M tokens

Contexto

1M ctx; batch $1/$5; cache read $0.10

DeepSeek V4.1 Flash

DeepSeek

Condicional

DeepSeek V4.1 Flash, the model now behind DeepSeek's deepseek-flash API, is a strong-value open-weight pick: MIT-licensed weights, image input, a 1M-token context and an Artificial Analysis score well above average for comparable models. Conditional because its standout coding-agent results are DeepSeek's own, Artificial Analysis measured it as very verbose, and peak hours double the rate. Right for cost-sensitive pipelines that can run off-peak or self-host; wrong for buyers who need independently verified agent performance before committing.

Entrada

$0.15 / 1M tokens

Salida

$0.60 / 1M tokens

Contexto

1M tokens; 2x price at weekday peak hours

Conditional. Eleven v4 is ElevenLabs' long-form text-to-speech model (id eleven_v4), covering 90+ languages with multi-speaker dialogue and voice cloning, and accepting up to 10,000 characters per request. The deciding caveat is price: $0.022 per 1K characters is a 72%-off promo that ends Oct 12 against a $0.08 list rate, and the quality claims are ElevenLabs' own, untested by us. Suits teams producing content and long-form audio who budget at list price.

Entrada

$0.08 / 1K characters

Salida

Billed per character (single rate)

Contexto

List $0.08 / 1K chars; 10K char limit

Conditional. Eleven v4 Turbo (id eleven_v4_turbo) is ElevenLabs' real-time speech model, stating a median inference latency of about 100 ms, excluding application and network latency, across 90+ languages via a Text to Dialogue WebSocket. The deciding caveat is that the latency figure is vendor-stated and untested by us, and $0.011 per 1K characters is a promo ending Oct 12 against a $0.04 list rate. Suits builders of voice agents and interactive characters.

Entrada

$0.04 / 1K characters

Salida

Billed per character (single rate)

Contexto

List $0.04 / 1K chars; median latency ~100 ms

FLUX 3

Black Forest Labs

Condicional

FLUX 3 is Black Forest Labs' unified multimodal model for image, video, audio and robot-action prediction. Its Video component is now pay-as-you-go through BFL's dashboard and API, from $0.06 per second at Draft HD to $0.80 at UHD, with five seconds of Standard HD costing $0.85. Conditional because every preference result is BFL's own, Image and Audio are not yet released, and the open-weight FLUX 3 Dev is still listed as coming soon.

Entrada

$0.17 / sec (Standard HD text-to-video)

Salida

Included in per-second video rate

Contexto

Video GA pay-as-you-go; $0.06-$0.80/s by res

Gemini 3.1 Pro

Google

Condicional

El modelo Pro más capaz de Google disponible públicamente, con contexto de 1M tokens a precios competitivos. Generación anterior: Gemini 3.6 y 3.5 Flash ya lo superan en benchmarks de codificación y agentes a menor coste. Mantenlo si usas Google Cloud/Vertex AI; si no, la línea Flash o los competidores ofrecen más.

Entrada

$2 / 1M

Salida

$12 / 1M

Contexto

1M tokens

Gemini 3.8 Flash Cyber

Google

Condicional

Gemini 3.8 Flash Cyber is Google's most capable cybersecurity model, a defensive specialist already in production at Chrome Security, Cloud Vulnerability Research and partner Wiz, with frontier vulnerability-discovery and patching results at a fraction of the leaders' rollout cost. The deciding caveat is access: it is gated to vetted defenders through the Fairwind Program, with no public API or published rate card. We rate it conditional rather than caution like the sibling Gemini 3.5 Flash Cyber because 3.8 ships published benchmark figures and named production deployments where 3.5 had neither, even though both remain gated. Right for organizations that can qualify as trusted defenders; everyone else cannot buy it today.

Entrada

N/A (no public rate card)

Salida

N/A (no public rate card)

Contexto

Fairwind-gated; no public API

Gemini 3.8 Flash TTS

Google

Condicional

Conditional. Gemini 3.8 Flash TTS is Google's flagship text-to-speech model, available in the Gemini API with voice design, consented voice replication and SynthID watermarking on every clip. The deciding caveat is cost: today's paid rates are launch prices that double when the launch window closes, and its Hume AI leaderboard placements are Google-reported, not measured by us. Suits developers building expressive narration, character voices or dubbing who can budget for the post-launch rate.

Entrada

$0.50 / 1M (text)

Salida

$9.00 / 1M (audio)

Contexto

Launch rate to 2026-12-31; $1/$18 from 2027

Gemini 3.8 Flash-Lite TTS

Google

Condicional

Conditional. Gemini 3.8 Flash-Lite TTS is Google's cost tier for high-volume speech: stable in the Gemini API, built into Google Vids, and billed at the same text input rate as Flash TTS with a lower audio output rate. Google ranks it second only to Flash TTS on Hume AI's Overall Quality Index, but that ranking is Google-reported and its launch rates are temporary, doubling once the promotion ends. Suits voice-agent cascades and bulk narration where cost per clip matters more than acting range.

Entrada

$0.50 / 1M (text)

Salida

$6.00 / 1M (audio)

Contexto

Launch rate to 2026-12-31; $1/$12 from 2027

Gemini 3.8 Live

Google

Condicional

Gemini 3.8 Live is Google's default Live API model for low-latency voice agents that keep talking while tool calls finish in the background. Conditional because Google bills Gemini 3.8 Live Extended Thinking at the identical rate, and Artificial Analysis scores that sibling higher on its Speech to Speech Index, so you pay the same for less reasoning. Pick 3.8 Live only when turn latency matters more than reasoning depth: developers shipping real-time voice experiences on the Gemini API.

Entrada

$0.75 / 1M (text)

Salida

$4.50 / 1M (text)

Contexto

131K in, 65K out; audio $3/$12 per 1M

GLM-5.2

Z.ai

Condicional

El mejor modelo de código de pesos abiertos con contexto de 1M tokens y licencia MIT. Supera a GPT-5.5 en múltiples benchmarks a una fracción del costo, pero aún va por detrás de Claude Opus 4.8 en las tareas más difíciles de largo alcance.

Entrada

$1.40 / 1M tokens

Salida

$4.40 / 1M tokens

Contexto

1M tokens

GLM-5.3

Z.ai

Condicional

GLM-5.3 is Z.ai's open-weights coding and cyber-defense model on the GLM-5.2 base, with every gain from post-training. Pricing is published at $1.40 input / $4.40 output per 1M, the same as GLM-5.2, and the weights are now on Hugging Face. It stays conditional because its headline coding and cyber scores come from Z.ai's own evaluations: reach for defensive security and agentic automation, but audit it yourself before standardizing.

Entrada

$1.40 / 1M tokens

Salida

$4.40 / 1M tokens

Contexto

1M ctx; Flash $0.15/$0.50, launch promo ended

GPT-4o (Retired from ChatGPT, API-only)

OpenAI

Condicional

GPT-4o (May 2024) has been superseded by the GPT-5.x family and delisted from OpenAI's flagship API pricing page. It remains available through the API but is no longer a current-generation model. Use only where migration to GPT-5.x is blocked; otherwise, GPT-5.5 or GPT-5.4 offer better performance at comparable cost.

Entrada

$2.50 / 1M tokens

Salida

$10 / 1M tokens

Contexto

128K tokens

GPT-5.5-Cyber

OpenAI

Condicional

85.6% en CyberGym — la puntuación más alta de un modelo individual — pero con acceso restringido solo para defensores verificados.

Entrada

N/A

Salida

N/A

Contexto

Trusted Access for Cyber; not commercial API

GPT-5.6 Luna

OpenAI

Condicional

GPT-5.6 Luna is OpenAI's previous-generation budget model at $0.20 input and $1.20 output per 1M tokens short context, generally available through the API and Codex. Its successor GPT-6 Luna, released 22 September 2026, lists at $0.10/$0.50, so Luna is no longer the low-cost default for new OpenAI work. It remains conditional because benchmarks are vendor-reported and it lacks activation classifiers; OpenAI lists no deprecation, so existing pipelines need not migrate yet.

Entrada

$0.20 / 1M tokens

Salida

$1.20 / 1M tokens

Contexto

Short $0.20/$1.20 · long $0.40/$1.80 per 1M

GPT-5.6 Terra

OpenAI

Condicional

GPT-5.6 Terra is OpenAI's mid-tier workhorse: GPT-5.5-class capability on OpenAI's own claim, at $2.00 input and $12.00 output per 1M tokens at short context ($4.00 / $18.00 long) after the 20% price cut of 30 July 2026. It is generally available via the API and Codex. Remains conditional: all benchmarks are vendor-reported without independent reproduction, and Terra is not selectable in the standard ChatGPT model picker.

Entrada

$2.00 / 1M tokens

Salida

$12.00 / 1M tokens

Contexto

Short $2.00/$12.00 · long $4.00/$18.00 per 1M

GPT-5.6-Cyber

OpenAI

Condicional

GPT-5.6-Cyber es el modelo de ciberseguridad entrenado específicamente por OpenAI, construido sobre GPT-5.6 Sol y disponible exclusivamente a través del programa restringido Daybreak Red. Es el primer modelo en alcanzar el umbral de capacidad cibernética 'High' de OpenAI, con un rendimiento en cadenas de exploits y zero-days que supera ampliamente a los modelos de propósito general.

Entrada

$12.50 / 1M tokens

Salida

$75 / 1M tokens

Contexto

400K tokens

GPT-6 Astra

OpenAI

Condicional

Astra ships at $10/$50 per 1M tokens short context, $20/$75 long context, with a 1,050,000-token context window and 128K max output. On OpenAI's own reported benchmarks it leads on computer use, terminal work, long context and cyber. We previously placed it third on the Artificial Analysis Intelligence Index at 61.2; we could not source that figure and have withdrawn it, and Artificial Analysis publishes no Astra score, so we have no vendor-neutral general-intelligence ranking for it. Conditional on two constraints: Fast mode is unavailable under EU data residency, and OpenAI disclosed decreased monitorability versus GPT-5.6 Sol. Route to it by task; do not make it your default.

Entrada

$10 / 1M tokens

Salida

$50 / 1M tokens

Contexto

1.05M tokens; short-ctx standard rate

GPT-6 Luna

OpenAI

Condicional

GPT-6 Luna is OpenAI's new budget model and the cheapest way into GPT-6, at half GPT-5.6 Luna's input rate, with a 1.05M-token context and text and image input. Conditional because every published result is OpenAI's own and prompts over 272K input tokens bill at higher rates. GPT-5.6 Luna stays on the price list with no deprecation notice, so migration is optional. Right for teams running high-volume, everyday API work at scale.

Entrada

$0.10 / 1M tokens

Salida

$0.50 / 1M tokens

Contexto

1.05M ctx; over 272K $0.20/$0.75; cache $0.01

GPT-6 Sol

OpenAI

Condicional

GPT-6 Sol is the lower-priced companion to GPT-6 Astra and succeeds GPT-5.6 Sol at half its per-token rate, with a 1.05M-token context and 128K output. Conditional because every published score is OpenAI's own and prompts over 272K input tokens bill at higher rates. GPT-5.6 Sol stays on the price list with no deprecation notice, so nothing forces a migration. Right for teams routing hard coding and agent work to OpenAI.

Entrada

$2 / 1M tokens

Salida

$10 / 1M tokens

Contexto

1.05M ctx; over 272K $4/$15; cache $0.20

GPT-6.1 Sol

OpenAI

Condicional

Conditional on evidence: GPT-6.1 Sol is OpenAI's model for complex coding, computer use and professional work, which OpenAI itself describes as near-Astra performance at a lower cost. We could not read the launch post, so no benchmark is stored and the quality claim is OpenAI's alone. Prompts past 272K input tokens bill at higher rates, and reasoning cannot be set to none or minimal. Suits teams building agents on the Responses API who will run their own evals first.

Entrada

$2 / 1M tokens

Salida

$10 / 1M tokens

Contexto

1.05M ctx; over 272K $4/$15; cache $0.10

GPT-Live-1

OpenAI

Condicional

GPT-Live-1 is OpenAI's full-duplex voice model: it listens and speaks at the same time and hands reasoning and tool use to a backend model. Since 10 September 2026 it is generally available in the API on the Live endpoint at $0.05 per minute, with backend model and tool usage billed separately. Conditional because its benchmarks are OpenAI's own, language quality is uneven, and real cost per call depends on the backend model you pair it with.

Entrada

$0.05 / minute (voice session)

Salida

Included in per-minute session rate

Contexto

Live API; backend model + tools billed separately

GPT-Live-1 mini

OpenAI

Condicional

La variante del nivel gratuito de GPT-Live-1 — la misma arquitectura dúplex completo en un paquete más pequeño y rápido, sirviendo como el modelo de voz predeterminado para usuarios de ChatGPT Free. Comparte las innovaciones centrales: interacción continua, soporte de palabra de activación y delegación a GPT-5.5. Se aplican las mismas limitaciones: sin API, calidad de idioma desigual. Una mejora sustancial sobre el antiguo modo de voz basado en turnos para usuarios gratuitos.

Entrada

Free (ChatGPT)

Salida

Free (ChatGPT)

Contexto

ChatGPT Voice only

Grok 4.5

SpaceXAI

Condicional

Competitively priced coding and agentic model at $2/$6 per 1M tokens up to 200K tokens of context, doubling to $4/$12 above that, with a 500K window. xAI's published benchmarks place it mid-pack behind Fable 5 and GPT-5.5, though it leads Opus 4.8 on DeepSWE and Terminal-Bench 2.1. The real story is cost efficiency: 4.2x more token-efficient than Opus 4.8 on SWE-Bench Pro. Best for teams needing strong coding at a fraction of frontier pricing; xAI's docs list only US regions.

Entrada

$2 / 1M tokens

Salida

$6 / 1M tokens

Contexto

500K ctx; 200K+ $4/$12; cache $0.30 (200K+ $0.60)

Grok 4.6

SpaceXAI

Condicional

Grok 4.6 is SpaceXAI's frontier model for coding and agentic work at $2 input and $6 output per 1M tokens under 200K, with a 500K-token context; prompts of 200K or more bill at $4/$12. At launch it scored 61 on the Artificial Analysis Intelligence Index, tying GPT-5.6 Sol, but that is still one independent evaluator. Grok 4.7 now lists at the same price, so compare the two before committing new work.

Entrada

$2.00 / 1M tokens

Salida

$6.00 / 1M tokens

Contexto

500K ctx; 200K+ $4/$12; cache $0.50

Grok 4.7

SpaceXAI

Condicional

Grok 4.7 keeps Grok 4.6's price and speed, and xAI says it works longer on hard tasks and checks its own work more carefully. Conditional because every published score is xAI's own, prompts of 200K tokens or more bill at double the headline rate, and the Batch API is not supported. Right for coding teams already working in Cursor or Grok Build.

Entrada

$2.00 / 1M tokens

Salida

$6.00 / 1M tokens

Contexto

500K ctx; 200K+ $4/$12; fast variant 2x price

Grok Voice 3.0

SpaceXAI

Condicional

Grok Voice 3.0 is SpaceXAI's speech-to-speech model for real-time voice agents, priced at $0.08 per minute, the same as Grok Voice 2.0. Artificial Analysis shows the highest Speech-to-Speech Index score, 86.9, with 0.81 seconds to first audio, but xAI's other benchmark and customer figures are its own. Conditional because we have not tested it and the grok-voice-latest alias moved to it automatically. It suits teams building phone or in-app voice agents on a managed model.

Entrada

$0.08 / min of audio (speech-to-speech)

Salida

Included in per-minute audio rate

Contexto

Voice Agent API; $4.80 / hr

Grok Voice Think Fast 2.0

SpaceXAI

Condicional

El modelo speech-to-speech de nueva generación de SpaceXAI con una arquitectura de razonamiento paralelo que lo hace sustancialmente más inteligente que los modelos de voz convencionales.

Entrada

$0.08 / min of audio (speech-to-speech)

Salida

Included in speech-to-speech rate

Contexto

API-only

Grok Voice Transcribe 2.0

SpaceXAI

Condicional

Grok Voice Transcribe 2.0 is SpaceXAI's speech-to-text model at $0.10 per hour of audio in batch, with speaker labels, word timestamps and key terms included. Conditional because every accuracy figure is SpaceXAI's own: it says the model is twice as accurate as 1.0 and first among 32 streaming models on Artificial Analysis, and we could not check that leaderboard. Right for voice-agent and call-transcription developers who will test it on their own audio; we have not tested it.

Entrada

$0.10 / hour of audio (batch)

Salida

Included in per-hour audio rate

Contexto

Streaming $0.20 / hour of audio

Hy3

Tencent

Condicional

Apache 2.0 open-weight MoE agentic model (295B total, 21B active) with strong tool-calling reliability and anti-hallucination behavior, but coding trails GLM-5.2 and self-hosting demands 8+ GPUs. The free OpenRouter tier that ran through Jul 21 is gone; OpenRouter now lists six providers at $0.13-$0.20 input and $0.53-$0.80 output per 1M tokens. Best for self-hosted coding agents and long-context document work where permissive licensing matters more than absolute benchmark scores.

Entrada

$0.20 / 1M

Salida

$0.80 / 1M

Contexto

256K tokens; OpenRouter providers $0.13-$0.20 in / $0.53-$0.80 out; free tier ended

Inkling

Thinking Machines Lab

Condicional

Inkling es la razón más sólida hasta ahora para tomarse en serio la IA multimodal de pesos abiertos. Ofrece razonamiento y programación competitivos con la mejor seguridad de su clase en pesos abiertos y esfuerzo de razonamiento controlable, todo bajo licencia Apache 2.0. Pero Thinking Machines admite abiertamente que no es el más potente en general — la factualidad se queda atrás (SimpleQA 43.9%) y el autoalojamiento exige hardware serio (2 TB de VRAM). conditional: una base convincente para organizaciones que necesitan poseer y afinar un modelo multimodal, no para equipos que buscan el máximo rendimiento sin personalización.

Entrada

$1.87 / 1M tokens

Salida

$4.68 / 1M tokens

Contexto

Up to 1M tokens native; Tinker 64K and 256K tiers; rates at 50% limited-time discount (list $3.74 / $9.36)

Kimi K3

Moonshot AI

Condicional

Moonshot AI's open-weight MoE model (Kimi K3 License, weights on Hugging Face) offers a 1M-token context at $3/$15 per 1M tokens and holds #1 on Arena WebDev (preliminary), but still trails Fable 5 and GPT-5.6 Sol on precise execution, and serving the weights needs 64+ accelerators. The rating stays conditional on legal risk: on July 22, 2026 the White House OSTP accused Moonshot of distilling Fable 5 and Treasury threatened sanctions. We have not re-verified that dispute's status this run.

Entrada

$3.00 / 1M

Salida

$15.00 / 1M

Contexto

1M ctx, $0.30 cached. Weights live (Jul 27).

Kolibri-1 is Aleph Alpha's English-German mixture-of-experts model with Apache 2.0 weights on Hugging Face, and a credible open-weight option for teams that must run German-language workloads on their own hardware. The catch is operations: the FP8 weights need about 78 GB of GPU memory, the pages we read name no hosted API or price, and every benchmark comes from Aleph Alpha's own harnesses. Right for public-sector and industrial teams that can self-host. Skip it for hosted-API needs or other languages.

Entrada

Free (open weights)

Salida

Free (open weights)

Contexto

262K native, 1M extrapolated; ~78 GB FP8

Laguna S 2.1

poolside

Condicional

Laguna S 2.1 es el primer modelo de programación occidental de pesos abiertos creíble en 11 meses: un MoE de 118B que activa solo 8B de parámetros por token y alcanza un 70.2% en Terminal-Bench 2.1, superando a modelos 10 veces más grandes. Pero no está en la frontera — GPT-5.6 Sol y Kimi K3 van muy por delante — y entre sus limitaciones conocidas figuran el sobreajuste a benchmarks, errores al anidar JSON en argumentos de herramientas y la ausencia de control configurable del esfuerzo de razonamiento. El colapso de la ronda Serie C de $14B de Poolside plantea dudas sobre su sostenibilidad, lo que hace que este modelo sea más adecuado para programación agéntica autoalojada donde la soberanía de datos pesa más que el liderazgo absoluto en benchmarks.

Entrada

$0.10 / 1M

Salida

$0.20 / 1M

Contexto

OpenMDW-1.1 license, 1M context

Llama 4 Maverick

Meta

Condicional

El modelo de código abierto líder para equipos que necesitan autoalojamiento, soberanía de datos o quieren evitar la dependencia de un proveedor de API.

Entrada

Free (self-hosted) or $0.20 / 1M tokens (hosted)

Salida

Free (self-hosted) or $0.60 / 1M tokens (hosted)

Contexto

1M tokens

MAI-Code-1-Flash

Microsoft

Condicional

MAI-Code-1-Flash was Microsoft's first in-house coding model, a sparse MoE priced at $0.75/$4.50 per 1M tokens. GitHub retired it from Copilot on 10 September 2026 and names MAI-Code-1.1-Flash, at $0.20/$1.20, as the replacement; it no longer appears in Copilot's supported-models or pricing tables. Copilot users should switch to 1.1-Flash, which is cheaper and scores higher on Terminal-Bench 2.1.

Entrada

$0.75 / 1M tokens

Salida

$4.50 / 1M tokens

Contexto

Retired from Copilot Sep 10 2026; 256K ctx

MAI-Code-1.1-Flash

Microsoft

Condicional

MAI-Code-1.1-Flash es el modelo de codificación renovado de Microsoft para el nivel pequeño de Copilot: un cuarto del costo y un 22% mejor en Terminal-Bench 2.1 que su predecesor de junio, ahora con visión nativa. Está pensado para trabajo iterativo de alto volumen más que para razonamiento de frontera, lo que lo convierte en el modelo de codificación serio más barato de Copilot. Recurre a él para autocompletados cotidianos, refactorizaciones y depuración asistida por imágenes; usa un buque insignia para arquitecturas complejas.

Entrada

$0.20 / 1M

Salida

$1.20 / 1M

Contexto

256K context

MAI-Cyber-1-Flash

Microsoft

Condicional

Microsoft's first in-house cybersecurity model, built on the MAI-Thinking-1 family and embedded inside the MDASH multi-agent harness, handles about 90% of security workloads at roughly half the cost of prior configurations and reserves GPT-5.4 for the hardest 10%. Microsoft reports 96% on CyberGym by the any-crash metric and 86.3% by the stricter final-submission metric, both from a tuned full-system configuration rather than an independent model-versus-model test. Available only through Azure AI Foundry with vetted enterprise access; no standalone pricing or public API.

Entrada

N/A (MDASH SCU consumption)

Salida

N/A (MDASH SCU consumption)

Contexto

Azure AI Foundry vetted access

Conditional. Mercury 2.5 is Inception's diffusion LLM, and raw output speed is the reason to pick it: Artificial Analysis ranks it among the fastest models it measures, and it ships tunable reasoning, parallel tool calls and structured outputs. The deciding caveat is quality: Artificial Analysis places its intelligence just below the median, and Inception's parity claims name no benchmark. Suits latency-bound voice agents, RAG pipelines and coding subagents, not hard reasoning.

Entrada

$0.20 / 1M tokens

Salida

$0.75 / 1M tokens

Contexto

260K ctx; 80% off at launch: $0.04/$0.15

Mistral Large 4

mistral

Condicional

Conditional: Mistral Large 4 is a public preview, not a finished release, since Mistral says its reinforcement learning run is still in flight and promises weights "by the end of the month". It is a mixture-of-experts model of about 1 trillion parameters, 52B active, with a 1M context on its docs page and a $1.36 input, $4.18 output list price per 1M tokens. Most benchmarks are Mistral's own. Trial it now if you want an open-weight-bound model, but wait for weights and licence before committing.

Entrada

$1.36 / 1M tokens

Salida

$4.18 / 1M tokens

Contexto

1M ctx; preview; sale $0.68/$2.09 on docs

Muse Glimmer

Meta

Condicional

Muse Glimmer es el modelo agentivo open-weight de 30B de Meta, destilado del modelo frontier cerrado Muse Spark y publicado bajo Apache 2.0. Con cuantización a 4-bit ejecuta llamadas a herramientas multi-paso, razonamiento multimodal y recuperación ante fallos en una sola GPU de consumo de 24 GB sin dependencias de la nube.

Entrada

Free (open weights)

Salida

Free (open weights)

Contexto

131K tokens

Muse Spark 1.1

Meta

Condicional

El primer modelo de IA de pago de Meta y su primera incursión en el mercado de programación comercial: $1.25/$4.25 por 1M tokens con 1M de contexto, orquestación nativa de subagentes, soporte MCP/herramientas y capacidad de uso de ordenador, aproximadamente 4 veces por debajo del precio de Anthropic/OpenAI. Lidera en benchmarks de uso de herramientas pero se queda 7 puntos por detrás de Opus 4.8 en programación pura en SWE-Bench Pro. Pesos cerrados, vista previa pública solo en EE. UU. Ideal para equipos que priorizan la orquestación de herramientas a bajo coste.

Entrada

$1.25 / 1M tokens

Salida

$4.25 / 1M tokens

Contexto

1M tokens

Muse Spark 1.2

Meta

Condicional

La actualización del modelo de Meta enfocado en codificación, co-entrenado con el harness de Muse Code — 82.9% en Terminal-Bench 2.1 y 59.3% en DeepSWE 1.1, solo superado por Claude Opus 5 en el primero. Precios estándar sin cambios a $1.25 entrada / $4.25 salida por 1M tokens.

Entrada

$1.25 / 1M tokens

Salida

$4.25 / 1M tokens

Contexto

1M tokens

Muse Spark 1.3

Meta

Condicional

Muse Spark 1.3 is Meta's strongest coding and long-context model yet, and an easy drop-in for anyone already on 1.2: the standard token price is unchanged while software-engineering and million-token retrieval results move sharply up. The deciding caveat is that the headline agent numbers come from a max reasoning configuration Meta has not released, while the shipping tier runs slower and costs more per task. Right for cost-sensitive coding teams inside Muse Code; wrong for anyone who needs independently reproduced benchmarks.

Entrada

$1.25 / 1M tokens

Salida

$4.25 / 1M tokens

Contexto

1M ctx; contributor tier $0.10/$0.20

Muse Spark Open

Meta

Condicional

Muse Spark Open is Meta's open-weight release of Muse Spark, an 816B mixture-of-experts model with 42B active parameters and a 1M-token context, available as downloads and from seven hosted providers. Conditional: the Muse Model License has limited commercial terms we did not read, the Meta pages we read give no hosted price, and Meta says its full evaluation report is still to come. It suits teams that want to self-host or shop between hosts, not buyers who need audited terms or independent benchmarks.

Entrada

Free (open weights)

Salida

Free (open weights)

Contexto

1M ctx; Muse Model License (limited commercial terms); no hosted price read

Muse Wonder

Meta

Condicional

Muse Wonder is Meta's most capable model on its API, but it is still a preview and we could not read a single benchmark score behind the launch claims. Its list price is 3.2x Muse Spark 1.3 on input and 4.7x on output, and Meta says the full safety report is still to come. It suits teams already on Muse Spark who want to test it on long-horizon agent work, not buyers who need independently checked results.

Entrada

$4.00 / 1M tokens

Salida

$20.00 / 1M tokens

Contexto

1M ctx; preview; cached $0.20

Mythos 5 (Claude Mythos 5)

Anthropic

Condicional

El modelo de ciberseguridad más potente del mundo (83.8% en CyberGym), construido sobre los pesos de Fable 5 con los clasificadores de seguridad retirados. El acceso se suspendió tras la directiva de exportación del 12 de junio; se restauró parcialmente el 26 de junio para ~100 organizaciones estadounidenses designadas de infraestructura crítica (Project Glasswing). El veredicto sigue CONDICIONAL: la capacidad es de élite, pero el acceso está sujeto a designación federal. No es una API pública: solo puede usarse si la organización figura en la lista del Departamento de Comercio.

Entrada

$10 / 1M tokens

Salida

$50 / 1M tokens

Contexto

1M tokens (restricted access)

Ornith-1.0

DeepReinforce

Condicional

Una sólida familia de modelos de código agentivo de código abierto con licencia MIT que logra benchmarks competitivos con la frontera — supera a Claude Opus 4.7 tanto en Terminal-Bench 2.1 como en SWE-Bench Verified — pero requiere self-hosting con recursos GPU significativos y proviene de un laboratorio nuevo con un historial limitado.

Entrada

Free (MIT license)

Salida

Free (MIT license)

Contexto

256K tokens

Palmyra X6

Writer

Condicional

Palmyra X6 es el modelo agéntico buque insignia de Writer para flujos de trabajo de marketing e ingresos — post-entrenado sobre el GLM-5.2 de pesos abiertos de Z.ai a $2/$8 por 1M tokens, una fracción de la tarifa de los modelos de frontera. Cada cifra destacada proviene de las evaluaciones internas de Writer, y la procedencia de GLM-5.2 es una auténtica cuestión de aprovisionamiento. Adóptalo dentro de Writer para el trabajo de agentes GTM sensible al costo; busca en otra parte la capacidad general validada con benchmarks independientes.

Entrada

$2 / 1M

Salida

$8 / 1M

Contexto

1M context, 8K max output

Qwen-Image-2.1

Alibaba

Condicional

Qwen-Image-2.1 is Alibaba's open-weights model for both text-to-image generation and editing, with native transparent RGBA output and multi-image composition from up to 10 references. Conditional because the weights ship under the Qwen Research License, which allows non-commercial use only, and we found no readable benchmark scores. Right for researchers and hobbyists running image generation and editing locally through Diffusers.

Entrada

Free (non-commercial weights)

Salida

Free (non-commercial weights)

Contexto

Qwen Research License; non-commercial

Qwen3.8-27B

Alibaba

Condicional

Qwen3.8-27B es el modelo open-weight de 27 000 millones de parámetros de Alibaba, ya disponible bajo Apache 2.0 con 262K de contexto nativo y despliegue en una sola GPU. Es el compañero autoalojable del buque insignia Qwen3.8-Max de 2,4T. Los benchmarks siguen siendo cifras de Alibaba, por lo que queda en 'conditional': un modelo real y ejecutable cuyas ganancias en programación declaradas por el fabricante aún esperan reproducción independiente.

Entrada

Free (open weights — self-hosted)

Salida

Free (open weights — self-hosted)

Contexto

262K native ctx, 1M extended; Apache 2.0

Qwen3.8-Omni-Flash

Alibaba

Condicional

Qwen3.8-Omni-Flash takes text, images, audio and video in one call with a 1M-token context, and Alibaba says it cut the per-hour price of audio input by more than 98% against the previous version. Conditional because every benchmark we found is Alibaba's own and the model answers in text only; spoken replies need a separate model, such as the Realtime variant, at higher rates. Right for teams building audio-visual agents on Alibaba Cloud.

Entrada

$0.15 / 1M

Salida

$0.47 / 1M (text)

Contexto

1M ctx; cache hit $0.016/1M; International

Sakana Fugu

Sakana AI

Condicional

Orquestador multi-agente que iguala a modelos frontera en benchmarks clave enrutando a través de un pool de agentes expertos — pero el enrutamiento opaco y la dependencia de plataforma limitan la transparencia.

Entrada

$5 / 1M tokens

Salida

$30 / 1M tokens

Contexto

272K tokens (>272K: $10/$45 per 1M)

SWE-2

Cognition

Condicional

SWE-2 is Cognition's coding model for Devin, post-trained from Kimi K3, and Cognition claims it lands within one point of Fable 5.1 on FrontierCode 1.1 Main at 64% lower cost. Conditional because every SWE-2 score is vendor-reported, the same table shows it far behind Fable 5.1 and GPT-6 Astra on Terminal-Bench 4, and it runs only inside Devin. Right for Devin Desktop and CLI users; wrong for anyone who needs an API model or independently verified results.

Entrada

N/A (no standalone API)

Salida

N/A (no standalone API)

Contexto

Devin only; Enterprise $0.75 in/$3.75 out per 1M

Ternary Bonsai 2 27B

PrismML

Condicional

Ternary Bonsai 2 27B squeezes Qwen3.8 27B into about 5.9GB at 1.76 effective bits, so a 262K-context text-and-image model fits on a Mac or a single consumer GPU under Apache 2.0. Conditional because the quality figures are PrismML's own, its blog and model card report different aggregate scores, and the files need PrismML's custom kernels: stock llama.cpp will not run them. Right for local-inference users short on memory.

Entrada

Free (open weights)

Salida

Free (open weights)

Contexto

262K ctx; self-hosted; PrismML kernels required

Gemini 3.5 Flash Cyber

Google

Precaución

Gemini 3.5 Flash Cyber es el primer modelo especializado en ciberseguridad de Google, afinado a partir de 3.5 Flash para encontrar, validar y parchear vulnerabilidades. Dentro de la arquitectura multiagente de CodeMender, alcanza un rendimiento competitivo en CyberGym frente a modelos mucho más grandes como Mythos a una fracción del coste. Pero las restricciones son severas: se ejecuta exclusivamente dentro de CodeMender, disponible solo para gobiernos y socios de confianza mediante un piloto de acceso limitado sin API pública, sin cifras de benchmark publicadas y sin calendario para un lanzamiento más amplio.

Entrada

N/A

Salida

N/A

Contexto

CodeMender-only, government-gated pilot

Gemini 3.5 Pro

Google

pending

El modelo frontera de Google previo a la disponibilidad general, ya en su cuarto aplazamiento y «con meses de retraso» según Bloomberg. El contexto de 2M tokens, el pipeline multimodal nativo y el razonamiento Deep Think siguen siendo capacidades reales, pero no existe un calendario de disponibilidad general confirmado. La capacidad de código es la carencia principal.

Entrada

Not yet published

Salida

Not yet published

Contexto

Est. $5-15/$30-60 per 1M. 2M ctx. Not GA.

Gemini 4

Google

pending

El modelo de próxima generación confirmado de Google DeepMind. El pre-entrenamiento comenzó el 21 de julio de 2026. Sin benchmarks, sin precios, sin especificaciones, sin fecha de GA.

Entrada

$2 / 1M tokens (through Nov 30)

Salida

$10 / 1M tokens (through Nov 30)

Contexto

$2/$10 to Nov 30, then $4/$20; paid tier only

Qwen3.8-Max

Alibaba

pending

Buque insignia MoE multimodal de 2.4 billones de parámetros. Todavía no en GA: sin precios de API por token, sin tabla de benchmarks, sin pesos abiertos publicados. Entrada desde $6/mes mediante Token Plan Lite.

Entrada

$2.00 / 1M tokens

Salida

$6.00 / 1M tokens

Contexto

Model Studio (Singapore); one tier up to 1M tokens