[whatmodel.sh](../../README.md) / Qwen3.5 Flash
# Qwen3.5 Flash
Alibaba · released 2026-02 · proprietary
**score 64.0** ±1.0 · #156 of 732 · from 9 benchmark results across 3 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Qwen3.5 Flash among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅▇█●▅▄▃▁ #175 of 469* 20% 1
chat & writing ▁▁▁▃▆▄▆█▆●▇▃ #119 of 402* 11% 1
math ▁▁▃▅█▆●█▄▂▁▁ #163 of 431* 41% 2
coding · #175 of 469 · 20% of its score
Beats [Qwen3-Coder-Next (80B-A3B)](qwen3-coder-next.md), [Gemini 2.5 Pro](gemini-2-5-pro.md) here, though they rank higher overall. Trails [QwQ-32B-Preview](qwq-32b-preview.md), [Ministral 3 8B Reasoning 2512](ministral-3-8b-reasoning.md), [Phi-4-reasoning 14B](phi-4-reasoning.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1243.7 ▁▁●▂▅█▃▆▅▅▁▂ beats 12/129 avg 981 20% sharp
chat & writing · #119 of 402 · 11% of its score
Beats [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [Step 3.5 Flash (196B-A11B)](step-3-5-flash.md), [GPT-5 mini](gpt-5-mini.md) here, though they rank higher overall. Trails [Nemotron-Cascade-8B](nemotron-cascade-8b.md), [Mistral Large 3 (675B-A41B)](mistral-large-3.md), [Gemini 2.5 Flash](gemini-2-5-flash.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1396.0 ▁▁▁▂▃▃▃▆▆●█▃ beats 242/385 avg 1260 11% blunt
math · #163 of 431 · 41% of its score
Beats [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md), [MiniMax-M2.7](minimax-m2-7.md), [MiniMax-M2.1](minimax-m2-1.md) here, though they rank higher overall. Trails [Olmo 3 7B Think](olmo-3-7b-think.md), [Qwen3-VL 4B Thinking](qwen3-vl-4b-thinking.md), [Nemotron 3 Nano 30B-A3B](nemotron-3-nano-30b-a3b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tiers 1–3 v2 9.5% ▂··▁●▃▄▄█▆▄▃ beats 6/86 very hard · avg 1.2% 33% sharp
OTIS mock AIME 2024–2025 84.4% ▃▃▄▃▃▃▇●█▃▂▅ beats 123/197 very hard · avg 7.2% 8.1% sharp · at its level · noisy
other tests (5)
test result vs the others in its run difficulty counts why
GPQA Diamond 82.3% ▁▁▁▁▂▄▆▄▅●█▅ beats 132/211 hard · avg 39% 18% sharp · at its level
Chess Puzzles (Epoch) 21.0% █▁▁▁▁▂●▃▃▂▁▁ beats 83/137 very hard · avg 5.8% 3.5% sharp · too hard for it · noisy
SimpleQA Verified 20.3% ▁▁▃▂●▃▆▆█▄▂▅ beats 13/81 very hard · avg 8.0% 3.3% at its level
Mystery Game Puzzles (Epoch) 20.0% █··▂▃●▄█▂▄▂▁ beats 33/77 very hard · avg 9.4% 3.3% sharp · too hard for it · noisy
Vectara hallucination leaderboard… 89.5% ▁▂▁▂▅●▂▃▄▃▁▁ beats 41/98 very easy · avg 90% 0.0% blunt
source results share of the score
Epoch AI 6 69% ▇▇▇▇▇▇▇▇
LMArena leaderboard dataset 2 31% ▇▇▇▇
Vectara hallucination leaderboard 1 0% ▇
prior: pull toward the middle 0% ▇
weighted average = 64.0
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
## How to run it
### Through an API
api (Alibaba Cloud Model Studio) · $0.18/M blended · $0.1 in / $0.4 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), qwen3.5-flash (currently equivalent to qwen3.5-flash-2026-02-23), 0\
[interactive version](https://whatmodel.sh/model/qwen3-5-flash) · [JSON](https://whatmodel.sh/api?format=json&all=1)