[whatmodel.sh](../../README.md) / Qwen3.7 Flash # Qwen3.7 Flash Alibaba · released 2026-07 · closed weights **score 66.1** ±1.2 · #125 of 732 · from 5 benchmark results across 1 source Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Qwen3.7 Flash among every model on that task or test, worst to best. 
task  vs the others          rank  counts  tests
math  ▁▁▃▅█▆▄●▄▂▁▁   #140 of 431*     65%      2
math · #140 of 431 · 65% of its score Beats [Claude Sonnet 4.6](claude-sonnet-4-6.md), [MiniMax-M3](minimax-m3.md), [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md) here, though they rank higher overall. Trails [Olmo 3 32B Think](olmo-3-32b-think.md), [Nemotron-Cascade-8B](nemotron-cascade-8b.md), [Olmo 3.1 32B Think](olmo-3-1-32b-think.md) here, though they rank lower overall. 
test                       result  vs the others in its run    difficulty            counts  why
FrontierMath tiers 1–3 v2   19.3%  ▂··▁▁●▄▄█▆▄▃ beats 13/86    very hard · avg 1.2%     56%  sharp · at its level
OTIS mock AIME 2024–2025    86.7%  ▃▃▄▃▃▃▇▇●▃▂▅ beats 130/197  very hard · avg 7.2%    8.9%  sharp · noisy
other tests (3) 
test                          result  vs the others in its run    difficulty            counts  why
GPQA Diamond                   82.3%  ▁▁▁▁▂▄▆▄▅●█▅ beats 133/211  hard · avg 39%           21%  sharp · at its level
Mystery Game Puzzles (Epoch)   15.0%  █··▂●▇▄█▂▄▂▁ beats 21/77    very hard · avg 9.4%    6.5%  sharp · too hard for it · noisy
Chess Puzzles (Epoch)          23.0%  █▁▁▁▁▂▃●▃▂▁▁ beats 91/137   very hard · avg 5.8%    6.2%  sharp · noisy
## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md) 
source                         results  share of the score
Epoch AI                             5   99% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle             1% ▇
weighted average                        = 66.1
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) ## How to run it ### Through an API api (Alibaba Cloud Model Studio) · $0.055/M blended · $0.03 in / $0.13 out per 1M tokens · [alibabacloud.com](https://www.alibabacloud.com/help/en/model-studio/text-generation-model) [price source](https://www.alibabacloud.com/help/en/model-studio/model-pricing): USD per 1M tokens, Singapore (International), qwen3.7-flash (currently equivalent to qwen3.7-flash-2026-07-15), 0\ [interactive version](https://whatmodel.sh/model/qwen3-7-flash) · [JSON](https://whatmodel.sh/api?format=json&all=1)