# DeepSeek V4.1 Flash

DeepSeek, released 2026-09-10

**Verdict: conditional.** 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. Last verified 2026-10-26.

## Pricing

- Input: $0.15 / 1M tokens
- Output: $0.60 / 1M tokens
- Context: 1M tokens; 2x price at weekday peak hours

## Strengths

- High-volume API workloads at $0.15 input and $0.60 output per 1M tokens off-peak, with off-peak cache-hit input at $0.003 per 1M
- Scheduling around peak pricing: peak rates, twice off-peak, apply only 01:00-04:00 and 06:00-10:00 UTC Monday through Friday, and all other hours bill off-peak
- Self-hosting under the MIT licence, with the weights published on Hugging Face
- Terminal-style coding agents: DeepSeek's own max-effort table reports 90.6 on Terminal-Bench 2.1 and 74.2 on DeepSWE v1.1, the top score on both rows, ahead of Opus-5.0's 89.1 and 74.0
- Document and image understanding: Artificial Analysis lists text and image input, and DeepSeek's base-model table reports 95.6 on DocVQA
- Long-context work within a 1M-token window and up to 384K output tokens
- Terminal-Bench 3.0 and 4.0: DeepSeek's own table reports 30.0 and 31.2, against Opus-5.0's 43.3 and 51.8
- Hard expert-knowledge questions: DeepSeek's table reports 36.8 on HLE, against Opus-5.0's 56.3 and GPT-5.6 Sol's 44.5
- Tight output-token budgets: Artificial Analysis measured 250M output tokens to run its Intelligence Index, against a 140M median for open-weight models of similar size
- Assuming the headline agent score carries over to your harness: DeepSeek's own scaffold table ranges from 65.5 under OpenCode to 74.2 under mini-SWE on DeepSWE v1.1
- Broad factual recall: DeepSeek's base-model table reports 42.3 on SimpleQA-Verified, against 55.2 for V4-Pro-Base
- Image generation: Artificial Analysis lists text as its only output modality
- Treating the stored benchmark figures as current: DeepSeek's pricing page now lists the served version as DeepSeek-V4.1-Flash-1017, and its October 17, 2026 changelog says that update has stronger benchmark results and shorter outputs. The scores here are from the September 10 release, and we have not read the 1017 scores

## Benchmarks

- Artificial Analysis Intelligence Index: 40 (https://artificialanalysis.ai/models/deepseek-v4-1-flash)
- Terminal-Bench 2.1 (DeepSeek-run): 90.6 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- Terminal-Bench 4.0 (DeepSeek-run): 31.2 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- DeepSWE v1.1 (DeepSeek-run): 74.2 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- GPQA Diamond (DeepSeek-run): 90.9 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- HLE (DeepSeek-run): 36.8 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- CyberGym (DeepSeek-run): 88.1 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- Codeforces rating (DeepSeek-run): 3471 (https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)

## Sources

- [Artificial Analysis, DeepSeek V4.1 Flash (Reasoning, Max Effort)](https://artificialanalysis.ai/models/deepseek-v4-1-flash)
- [DeepSeek API Docs: DeepSeek-V4.1-Flash Release (2026/09/10)](https://api-docs.deepseek.com/news/news260910)
- [Hugging Face, deepseek-ai/DeepSeek-V4.1-Flash model card (official, MIT)](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)
- [DeepSeek API Docs: Models and Pricing](https://api-docs.deepseek.com/quick_start/pricing/)
- [DeepSeek API changelog (V4 Pro API service continues after Sep 14, 2026)](https://api-docs.deepseek.com/updates)
- [DeepSeek API Docs: DeepSeek-V4.1-Flash-1017 update (2026/10/17)](https://api-docs.deepseek.com/news/news261017)

Canonical: https://neomanex.com/models/deepseek-v4-1-flash