# Gemini 3.8 Flash

Google, released 2026-09-02

**Verdict: recommended.** 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. Last verified 2026-09-03.

## Pricing

- Input: $0.75 / 1M
- Output: $3.75 / 1M
- Context: 1M context, 64K output

## Strengths

- Long-horizon software engineering — DeepSWE v1.1 73.7% on Google's chart (74% ±1 on the independent leaderboard at high effort), up from 65.3% for 3.7 Flash
- Autonomous agents and computer use — Terminal-Bench 4.0 19.1% vs 11.2% for 3.7, OSWorld 2.0 59.0% vs 50.6%
- Knowledge-dense professional domains — HLE-Verified 54.9%; leads 3.7 and other frontier models on Vals Finance Agent V2 (61.4%) and Harvey's Legal Agent Benchmark
- Google-ecosystem builders — stable GA ID gemini-3.8-flash in Gemini API, AI Studio, Antigravity, Android Studio, Gemini Enterprise; powers Gemini app, AI Mode and Gemini in Sheets
- Token-metered, latency-sensitive production — "works harder" means extra reasoning steps and iterative tool calls; Artificial Analysis measured ~40% higher cost per task than 3.7 ($0.40 to $0.58)
- Hardest frontier tasks — still trails Claude Opus 5 on Terminal-Bench 4.0 (19.1% vs 51.8%), OSWorld 2.0 (59.0% vs 75.4%) and GDP.PDF (35% vs 40% for GPT-5.6 Sol)
- Non-English production without requalification — model card reports a 5.4-point multilingual safety regression vs 3.7 (lower is better); Google calls it mostly false positives
- Teams needing price stability beyond 2026 — the introductory rate expires Dec 31, 2026, then doubles to $1.50/$7.50

## Benchmarks

- DeepSWE v1.1: 73.7% (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- DeepSWE v1.1 (independent leaderboard, high effort): 74% ±1 (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- Terminal-Bench 2.1: 89.4% (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- Terminal-Bench 4.0: 19.1% (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- OSWorld 2.0 (batch tool): 59.0% (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- HLE-Verified: 54.9% (https://blog.google/innovation-and-ai/models-and-research/gemini-models/3-8-flash-and-3-8-flash-cyber/)
- Vals Finance Agent v2: 61.4% (https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)
- Gray Swan indirect prompt injection (ASR@15): 5.5% (https://kingy.ai/blog/gemini-3-8-flash-cyber-benchmarks/)

## Sources

- [ExplainX — Gemini 3.8 Flash is official: benchmarks, Flash Cyber, and pricing](https://www.explainx.ai/blog/gemini-3-8-flash-launch-coding-benchmarks-2026)
- [Google — Introducing Gemini 3.8 Flash and 3.8 Flash Cyber](https://blog.google/innovation-and-ai/models-and-research/gemini-models/3-8-flash-and-3-8-flash-cyber/)
- [Kingy AI — Gemini 3.8 Flash Cyber benchmarks explained (Gray Swan / shared-core figures)](https://kingy.ai/blog/gemini-3-8-flash-cyber-benchmarks/)
- [Kingy AI — Gemini 3.8 Flash review: benchmarks, specs, pricing and verdict](https://kingy.ai/blog/gemini-3-8-flash-review-benchmarks-specs-pricing/)

Canonical: https://neomanex.com/models/gemini-3-8-flash