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Qwen3.5-Max-Preview

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Qwen3.5-Max-Preview is a closed-weights language model from Alibaba, released March 2026.

Catalogue identity notes

Comparison-only. Arena entry 'qwen3.5-max-preview' (text). Released 2026-03: Qwen blog post 'Qwen3.5-Max-Preview' dated 2026-03-19. Arena-only pre-release preview that Qwen publicly named; no Qwen3.5-Max API model or release was found, so no API is given.

72.4±3.3comparison only: no current run option verifiedfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Qwen3.5-Max-Preview, out of 1132 with a score, then more from Alibaba.

#modelscorewhereRAMreleased
73GPT-5 OpenAI72±1api $3.44/M2025-08
74Qwen3.6 Max Preview Alibaba72±1api $2.92/M2026-04
75Qwen3.5-Max-Preview Alibaba72±3comparison only2026-03
76Claude Sonnet 4.6 Anthropic72±1api $6.00/M2026-02
77Gemini 3 Flash (Preview) Google72±1api $1.13/M2025-12
more from Alibaba
18Qwen3.8 Max (2.4T-A95B) Alibaba78±1api $3.00/M +local~380GB2026-08
34Qwen3.8 Max (0902) Alibaba76±1api $3.00/M2026-09
37Qwen3.8-Flash-Next Alibaba75±1local~59GB2026-08

see all LLMs · find the ones that fit your machine

$ what it's good at

chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #46 of 579 * · 95% of its score · 1 test

Beats GPT-6 Sol, MiMo-V2.6-Flash (309B-A15B), GPT-6 Luna here, though they rank higher overall. Trails MiMo-V2.5-Pro (1T-A42B), Grok 4.20 (0309 reasoning), Claude Opus 4.5 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LMArena (text)1464.7 ✎▁▁▁▂▃▃▃▆▆▇█▃ beats 335/379avg 1268▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%blunt

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · LMArena leaderboard dataset 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The 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's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
LMArena leaderboard dataset1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%CC BY 4.0
prior · pull toward the middle▇ 5%
weighted average= 72.4

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json