[whatmodel.sh](../../README.md) / Qwen3.6 Plus
# Qwen3.6 Plus
Alibaba · released 2026-04 · closed weights
**score 68.9** ±0.8 · #89 of 732 · from 14 benchmark results across 7 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Qwen3.6 Plus among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄●▅▄▄▂▁ #120 of 313* 17% 2
coding ▁▁▁▃▅▇█▇▅●▃▁ #68 of 469* 25% 2
chat & writing ▁▁▁▃▆▄▆█▆▇●▃ #60 of 402* 6.4% 1
math ▁▁▃▅█▆▄█●▂▁▁ #69 of 431 33% 3
vision & documents ▁▁▂▂▁▃▄▂▆▇●▄ #28 of 153* 10% 2
agent tasks · #120 of 313 · 17% of its score
Beats [o3-pro](o3-pro.md), [Grok 4.3](grok-4-3.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Large](jamba-1-5-large.md), [Devstral 2 (2512)](devstral-2.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
SWE-bench Verified 57.9% ▁··▁·●▂▁▄█▄▁ beats 3/29 hard · avg 19% 14% sharp · at its level
Agents' Last Exam overall full-pa… 8.6% ▄···●▄▄▄█▄·█ beats 1/10 very hard · avg 1.9% 3.8% typical
coding · #68 of 469 · 25% of its score
Beats [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md), [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5.2](gpt-5-2.md) here, though they rank higher overall. Trails [MiMo-V2.5-Pro (1T-A42B)](mimo-v2-5-pro.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
SWE-bench Verified 57.9% ▁··▁·●▂▁▄█▄▁ beats 3/29 hard · avg 19% 14% sharp · at its level
Arena WebDev (Code Arena) 1461.6 ▁▁▃▂▅█●▆▅▅▁▂ beats 63/129 avg 981 11% sharp
chat & writing · #60 of 402 · 6.4% of its score
Beats [Claude Haiku 5.5](claude-haiku-5-5.md), [GPT-6 Luna](gpt-6-luna.md), [Grok 4.7](grok-4-7.md) here, though they rank higher overall. Trails [Gemma 4 31B](gemma-4-31b.md), [Gemini 2.5 Pro](gemini-2-5-pro.md), [Claude Sonnet 4.5](claude-sonnet-4-5.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1443.0 ▁▁▁▂▃▃▃▆▆▇●▃ beats 310/385 avg 1260 6.4% blunt
math · #69 of 431 · 33% of its score
Beats [Claude Sonnet 4.6](claude-sonnet-4-6.md), [Claude Opus 4.5](claude-opus-4-5.md), [Qwen3.7 Plus](qwen3-7-plus.md) here, though they rank higher overall. Trails [INTELLECT-3](intellect-3.md), [GPT-5 mini](gpt-5-mini.md), [Qwen3-Coder-Next (80B-A3B)](qwen3-coder-next.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tiers 1–3 v2 38.2% ▂··▁▁▃▄●█▆▄▃ beats 28/86 very hard · avg 1.2% 29% sharp · at its level
OTIS mock AIME 2024–2025 93.3% ▃▃▄▃▃▃▇▇●▃▂▅ beats 155/197 very hard · avg 7.2% 2.5% sharp · noisy
MathConstraint full release, no t… 47.4% ▄··▄▄·▄▄●▄·▄ beats 6/8 very hard · avg 11% 1.4% at its level
vision & documents · #28 of 153 · 10% of its score
Beats [Claude Sonnet 5.5](claude-sonnet-5-5.md), [GPT-6 Sol](gpt-6-sol.md), [MiMo-V2.6-Pro](mimo-v2-6-pro.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
CharXiv (reasoning questions) (ma… 81.5% ▄▂▄▆▄▄▆··●█▂ beats 16/21 medium · avg 38% 8.3% typical
BEAR-Bench (bilingual RU/EN enter… 65.0% ▃▃·▅·▃·█·█●▅ beats 11/14 hard · avg 24% 2.1% at its level
other tests (5)
test result vs the others in its run difficulty counts why
GPQA Diamond 88.4% ▁▁▁▁▂▄▆▄▅▇●▅ beats 164/211 hard · avg 39% 7.4% sharp
Mystery Game Puzzles (Epoch) 12.0% █··●▃▇▄█▂▄▂▁ beats 19/77 very hard · avg 9.4% 4.5% sharp · noisy
Chess Puzzles (Epoch) 17.0% █▁▁▁▁▂●▃▃▂▁▁ beats 72/137 very hard · avg 5.8% 3.7% sharp · noisy
AgentWorldBench (open-ended, over… 50.8% ▄▄··●▄·▄█▄██ beats 2/11 hard · avg 26% 3.3% blunt · at its level
SimpleQA Verified 44.1% ▁▁▃▂▃▃▆●█▄▂▅ beats 41/81 very hard · avg 8.0% 2.3% at its level
source results share of the score
Epoch AI 7 63% ▇▇▇▇▇▇▇▇
LMArena leaderboard dataset 2 18% ▇▇
Qwen (submitted / maker-reported) 1 8% ▇
Agents' Last Exam 1 4% ▇
Qwen/Qwen-AgentWorld-35B-A3B model card… 1 3% ▇
BEAR-Bench: A Bilingual Enterprise and … 1 2% ▇
MathConstraint: Automated Generation of… 1 1% ▇
prior: pull toward the middle 0% ▇
weighted average = 68.9
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/)) · Agents' Last Exam ([CC BY 4.0](../../licenses/paper-2606.05405v2-CC-BY-4.0.txt)) · Qwen/Qwen-AgentWorld-35B-A3B model card ([Apache-2.0](https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B/blob/60d2b0434a53d2e62a7c00a489586815d94ebffb/README.md)) · BEAR-Bench: A Bilingual Enterprise and Academic Reasoning Benchmark for Multimodal Models ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs ([CC BY 4.0](../../licenses/paper-2605.08498v1-CC-BY-4.0.txt))
## How to run it
### Through an API
api (Together AI) · $1.13/M blended · $0.5 in / $3 out per 1M tokens · [docs.together.ai](https://docs.together.ai/docs/serverless-models)
[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/togetherai/models/Qwen/Qwen3.6-Plus.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/alibaba/qwen3.6-plus.toml)
[interactive version](https://whatmodel.sh/model/qwen3-6-plus) · [JSON](https://whatmodel.sh/api?format=json&all=1)