Qwen3.8-Max-0902

Released

Qwen3.8-Max-0902 is an AI model released by Qwen on Wednesday, Sep 2 2026, 7 days after Qwen3.8-Flash-Next. It is a 2.4T parameter model with a 1M token context window. Benchmark results (shown below) cover QwenSWEBench V2, CoWorkBench, DeepSWE 1.1, NL2Repo-Bench, Terminal-Bench 4.0, Terminal-Bench 3.0, and 4 more.

Benchmarks

Coding

QwenSWEBench V2Software engineering — Qwen's in-house coding benchmark, second version, built around complex real-world software-engineering tasks. Scores are not comparable with the first version. Higher is better.
70%
#1
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better.
69.3%
#13 of 36
NL2Repo-BenchRepo-level code generation — Tests whether the AI can turn a natural-language requirement into working code across an entire repository, not just produce a single function or patch. Higher is better.
64.9%
#3 of 7

Terminal & CLI

Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better.via Terminal-Bench
26.97%
#19 of 29
Terminal-Bench 3.0Agentic terminal coding — command-line task completion (v3.0, much harder task set)
29%
#2 of 7

Agentic & tool use

CoWorkBenchLong-horizon office work — Tests long-running office tasks across fields including computer science, finance, law, medicine, and other productivity work. Higher is better.
76.1%
#1
JobBenchProfessional tool use — Tests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better.
64%
#4 of 11
Toolathlon-VerifiedPersonal tool use — Tests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better.
73.3%
#5 of 9
AutomationBenchBusiness workflows — Tests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better.
50.8%
#5 of 19

Multimodal

MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better.
82.7%
#2 of 12

Source: Terminal-Bench, retrieved 12 October 2026. Other sources are identified on the linked benchmark pages.

Compare Qwen3.8-Max-0902 with

Qwen3.8-Max-0902

About

Qwen3.8-Max-0902, released September 2, 2026, was a post-trained refresh of the Qwen3.8-Max Alibaba had shipped a month earlier rather than a new model underneath it. The 2.4-trillion-parameter base and the 1M-token context window were unchanged; what the lab changed was the post-training, which it said had been extended on coding and on Cowork, the agentic office work its own CoWorkBench measures. The dated suffix marked the checkpoint the way DeepSeek had been naming its own refreshes since V3-0324, and it kept the older checkpoint addressable instead of replacing it in place.

The launch table was set against the August checkpoint rather than against rival labs, and the coding rows carried most of the movement. Qwen3.8-Max-0902 scored 29.0% on Terminal-Bench 3.0 where the older checkpoint had managed 11.3%, 69.3% on DeepSWE 1.1 against 56.6%, and 64.9% on NL2Repo-Bench against 55.9%; on QwenSWEBench V2, Alibaba's own harder in-house set, it posted 70.0% to the earlier model's 55.1%, ahead of the 68.0% and 67.1% it reported for Claude Opus 5 and Fable 5. Agent work moved less. CoWorkBench went from 74.8% to 76.1% and Toolathlon-Verified from 72.5% to 73.3%, both still behind Claude Opus 5, while JobBench jumped from 53.4% to 64.0%. Multimodal scores were flat, at 82.7% on MMMU-Pro against 82.3%.

Pricing was $2 per million input tokens and $6 per million output, with cache hits at $0.17 explicit and $0.25 implicit — the first time the Max tier had been quoted on QwenCloud, the API Alibaba had introduced with Qwen3.8-Flash the previous week, rather than through Alibaba Cloud Model Studio. It launched API-only, with no weights published for the refreshed checkpoint, leaving the August base model the most recent Qwen3.8 weights available.

Frequently asked questions

Qwen3.8-Max-0902 was released by Qwen on Wednesday, Sep 2 2026.

All Qwen releases

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