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ModelTape / Models / Gemini 3.7 Flash
Google · API-only (closed weights)

Gemini 3.7 Flash

Gemini 3.7 Flash is an API-only (closed weights) language model from Google, released August 13, 2026. The context window is 1M tokens. On the Epoch Capabilities Index it scores 158.4, rank 25 of 256 rated models. API price: $0.75 input / $3.75 output per million tokens.

Today, we’re building on the progress of our widely used Flash series by introducing Gemini 3.7 Flash, our most intelligent workhorse model yet for coding and agents.

Check it against your own PC →

Lab
Google
Released
August 13, 2026
Weights
API-only (closed weights)
Parameters
–
Context
1M
Price / M tokens
$0.75 / $3.75 in / out
Epoch ECI
158.4 #25

Strengths by category

ModelTape's 0–100 fit on Epoch AI benchmark results.

CategoryScoreBased on
Reasoning32.1Chess Puzzles, Mystery Game Puzzles
Math57.3ProofBench, OTIS Mock AIME 2024-2025, FrontierMath-Tiers-1-3-v2-Private, FrontierMath-Tier-4-v2-Private
Coding57.4MirrorCode, FrontierSWE, DeepSWE
Knowledge82.7GPQA diamond, SimpleQA Verified

Benchmark results

Benchmark (Epoch AI)Score
OTIS Mock AIME97.2%
GPQA Diamond97.0%
FrontierMath (Tiers 1–3)75.3%
SimpleQA Verified69.2%
DeepSWE65.5%
Chess Puzzles64.2%
ProofBench58.0%
MirrorCode41.1%
FrontierMath-Tier-4-v2-Private36.6%
Mystery Game Puzzles30.6%
FrontierSWE20.3%
Remote Labor Index5.0%
Furniture Assembly0.0%

Links

Announcement · Epoch AI benchmarks

Models with a similar score

Muse Wonder · Kimi K3.1 Pro · GPT-5.6 Terra · Claude Haiku 5.5 · GPT-5.4 Pro · GPT-5.5 · Claude Opus 4.8 · DeepSeek V4.1 Flash 1017

More from Google

Gemini 4 Carbon · Gemini 4 Argon · Gemini 3.8 Flash · Gemini 3.6 Flash · Gemini 3.5 Flash-Lite · Gemini 3.5 Flash Cyber · Gemma 4 E4B · Gemma 4 E2B

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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