[whatmodel.sh](../../README.md) / Gemini 3.7 Flash
# Gemini 3.7 Flash
Google · released 2026-08 · closed weights
**score 74.8** ±0.5 · #36 of 732 · from 32 benchmark results across 9 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Gemini 3.7 Flash among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅▄●▂▁ #45 of 313 19% 8
coding ▁▁▁▃▅▇█▇▅▄●▁ #33 of 469 10% 4
chat & writing ▁▁▁▃▆▄▆█▆▇▇● #14 of 402* 3.0% 1
math ▁▁▃▅█▆▄█▄●▁▁ #27 of 431 45% 8
vision & documents ▁▁▂▂▁▃▄▂▆▇█● #5 of 153* 4.9% 2
agent tasks · #45 of 313 · 19% of its score
Trails [GLM-5.2](glm-5-2.md), [GLM-5.3-Flash](glm-5-3-flash.md), [Grok 4.7](grok-4-7.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena Agent (October 2026 aggrega… -0.0135 IPS ▁▁▁▃▃●█▁▂▂▁▁ beats 23/59 avg -0.379 IPS 7.8% sharp
Terminal-Bench 2.1 (maker) 81.6% ▁·▁·▁▁▄▃▆█▅● beats 55/63 hard · avg 25% 3.2% sharp · small run · several runs
Terminal-Bench 4.0 11.2% ●▅▅▅▅·▅▃▃▅▅▅ beats 0/20 very hard · avg 0.5% 3.0% sharp
SWE-bench Pro (split unspecified)… 60.4% ▂·▁▁▁▁▂▃█●▂▁ beats 44/58 very hard · avg 6.0% 1.9% sharp · at its level · small run
DeepSWE v1.1 (resolved) (maker) 65.3% ▂····▂▁▁▆●██ beats 12/31 hard · avg 25% 0.9% at its level · small run
KlinikeBench strict pass@1 (333 i… 10.8% ▁▁·▁▁▁▁▅●█▅█ beats 11/27 very hard · avg 2.4% 0.9% typical
Terminal-Bench 3.0 (maker) 14.9% █·█··█●····█ beats 3/4 very hard · avg 1.9% 0.5% small run
τ³-bench Banking (maker) 30.9% ▂▂·▅█▂▃▃▃▆▂● beats 22/24 very hard · avg 7.9% 0.4% blunt · small run
coding · #33 of 469 · 10% of its score
Beats [GPT-5.5](gpt-5-5.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [Claude Opus 4.8](claude-opus-4-8.md) here, though they rank higher overall. Trails [GLM-5.2](glm-5-2.md), [GLM-5.3-Flash](glm-5-3-flash.md), [Grok 4.7](grok-4-7.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1589.7 ▁▁▃▂▅█▃▆●▅▁▂ beats 98/129 avg 981 5.4% sharp
Luau Leetcode fully solved (Torpe… 79.8% ▁▁▁▁·▁▂▃▅▃●▇ beats 32/49 hard · avg 17% 2.0% sharp
SWE-bench Pro (split unspecified)… 60.4% ▂·▁▁▁▁▂▃█●▂▁ beats 44/58 very hard · avg 6.0% 1.9% sharp · at its level · small run
DeepSWE v1.1 (resolved) (maker) 65.3% ▂····▂▁▁▆●██ beats 12/31 hard · avg 25% 0.9% at its level · small run
chat & writing · #14 of 402 · 3.0% of its score
Beats [GPT-6 Astra](gpt-6-astra.md), [GPT-6.1 Sol](gpt-6-1-sol.md), [Claude Sonnet 5.5](claude-sonnet-5-5.md) here, though they rank higher overall. Trails [Muse Spark 1.2](muse-spark-1-2.md), [Muse Spark 1.1](muse-spark-1-1.md), [Claude Opus 4.6](claude-opus-4-6.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1489.6 ▁▁▁▂▃▃▃▆▆▇█● beats 372/385 avg 1260 3.0% blunt
math · #27 of 431 · 45% of its score
Beats [Gemini 3.8 Flash](gemini-3-8-flash.md), [DeepSeek V4.1 Flash](deepseek-v4-1-flash.md), [Grok 4.6](grok-4-6.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
FrontierMath tier 4 v2 36.6% ▁▂▁▂█●▂▃▂▁▁▁ beats 42/67 very hard · avg 0.1% 13% sharp · at its level
FrontierMath tiers 1–3 v2 71.6% ▂··▁▁▃▄▄█●▄▃ beats 62/86 very hard · avg 1.2% 13% sharp · at its level
MathArena ArXivMath June 2026 (48… 62.5% ▂···▄·█●▆▆▄▂ beats 7/19 very hard · avg 5.1% 6.4% sharp · at its level
MathArena ArXivMath April 2026 (4… 57.5% ▁·····▅█●▄·▁ beats 11/20 very hard · avg 7.6% 6.2% sharp · at its level
MathArena BrokenArXiv April 2026 … 19.3% ▂▂▆●▃▃▂▂▂··▂ beats 6/18 very hard · avg 0.8% 2.4% sharp · at its level · noisy
MathArena ArXivMath May 2026 (40 … 47.5% ▁··▁●█▄▁·▃·▁ beats 4/17 very hard · avg 11% 2.1% at its level
MathArena ArXivLean June 2026 (46… 21.7% ▄····▄▄█●█·▄ beats 5/9 very hard · avg 0.9% 1.7% sharp
OTIS mock AIME 2024–2025 97.2% ▃▃▄▃▃▃▇▇█▃●▅ beats 170/197 very hard · avg 7.2% 0.4% sharp · maxed out · noisy
vision & documents · #5 of 153 · 4.9% of its score
Beats [GPT-6 Astra](gpt-6-astra.md), [Claude Opus 5.5](claude-opus-5-5.md), [GPT-6.1 Sol](gpt-6-1-sol.md) here, though they rank higher overall. Trails [Claude Opus 4.7](claude-opus-4-7.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
CharXiv (reasoning questions) (ma… 84.5% ▃·▃·▃▃▃·▃▃●▅ beats 9/11 medium · avg 38% 2.9% typical
Arena vision (style controlled) 1295.2 ▁▁▂▂▂▂▃▄▅▅█● beats 148/152 avg 1061 2.0% blunt
other tests (10)
test result vs the others in its run difficulty counts why
Furniture Assembly (Epoch) 26.7% █●▆▆▆▂▆▂▂▂▂▅ beats 6/32 very hard · avg 1.2% 5.2% sharp · at its level
Mystery Game Puzzles (Epoch) 37.0% █··▂▃▇▄●▂▄▂▁ beats 59/77 very hard · avg 9.4% 5.0% sharp · noisy
Chess Puzzles (Epoch) 47.0% █▁▁▁▁▂▃▃▃●▁▁ beats 126/137 very hard · avg 5.8% 2.9% sharp · at its level · noisy
GPQA Diamond 94.8% ▁▁▁▁▂▄▆▄▅▇█● beats 207/211 hard · avg 39% 1.9% sharp
SimpleQA Verified 69.2% ▁▁▃▂▃▃▆▆█▄▂● beats 73/81 very hard · avg 8.0% 1.2% at its level
Icelandic LLM Leaderboard average… 65.0% ▁▁▃▂▂▄▁▃▄▄▄● beats 30/38 very hard · avg 14% 1.1% at its level
LVBench (maker) 85.4% ▇·█▅▅▄▄··●▁▁ beats 26/28 medium · avg 59% 0.9% typical
MRCR v2 8-needle, 128k (maker) 97.0% █▄▄█·▄···▄·● beats 8/8 medium · avg 53% 0.9% small run
MirrorCode (Epoch) 41.1% ▄·█▄▄▄█●·▄▄█ beats 9/13 very hard · avg 1.6% 0.8% sharp · at its level · noisy
RobloxQA v2.0 multiple choice (To… 96.8% ▁▁▃▁█▄▃▃●▂▂▂ beats 40/49 easy · avg 77% 0.7% maxed out
source results share of the score
Epoch AI 9 43% ▇▇▇▇▇
MathArena ArXivMath / BrokenArXiv / ArX… 5 19% ▇▇
LMArena leaderboard dataset 4 18% ▇▇
Google DeepMind Gemini model page and m… 6 8% ▇
Google Cloud developer's guides to Gemi… 4 4% ▇
Terminal-Bench 4.0 official leaderboard… 1 3% ▇
Roblox LLM Leaderboard 2 3% ▇
Miðeind Icelandic LLM Leaderboard 1 1% ▇
KlinikeBench: Evaluating Language Model… 1 1% ▇
prior: pull toward the middle 0% ▇
weighted average = 74.8
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · MathArena ArXivMath / BrokenArXiv / ArXivLean model-output datasets ([CC BY-SA 4.0](../../licenses/matharena-sharealike-NOTICE.txt)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Google Cloud developer's guides to Gemini 3.8 Flash and 3.7 Flash ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · Terminal-Bench 4.0 official leaderboard submissions ([Apache-2.0](../../licenses/terminal-bench-leaderboard-submissions-Apache-2.0.txt)) · Roblox LLM Leaderboard ([MIT](../../licenses/roblox-llm-leaderboard-MIT.txt)) · Miðeind Icelandic LLM Leaderboard ([CC BY 4.0](../../licenses/mideind-icelandic-llm-leaderboard-CC-BY-4.0.txt)) · KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))
## How to run it
### Through an API
api (Google) · $1.50/M blended · $0.75 in / $3.75 out per 1M tokens · [ai.google.dev](https://ai.google.dev/gemini-api/docs/models)
[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/google/models/gemini-3.7-flash.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/google/gemini-3.7-flash.toml)
[interactive version](https://whatmodel.sh/model/gemini-3-7-flash) · [JSON](https://whatmodel.sh/api?format=json&all=1)