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Qwen3.8 Max

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Ofoxqwen/qwen3.8-maxqwen

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Provider
Ofox
Model key
qwen/qwen3.8-max
Release date
Aug 3, 2026
Last updated
Aug 3, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.71
Output token cost
$5.14

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Qwen3.8 Max

Merge Gateway

CoverageBenchmark

Alibaba's Qwen3.8-Max open-weight release shipped as Qwen3.8-2.4T-A95B on Hugging Face and ModelScope on August 13, 2026, shortly after the August 2 QwenCloud API debut, with the dense Qwen3.8-27B sibling following on August 14. The model debuts under the headline "A New Bar for Coding and Cowork," positioning it at so Coverage situates the open-weight drop in a crowded September for frontier AI, with OpenAI, Anthropic, and Google all shipping new models within days, making Alibaba's decision to release weights outright the sharpest example yet of open source pushing back on closed labs. The article references an overall score of 86.

Merge Gateway

CoverageBenchmark

On September 2, 2026, Alibaba released Qwen3.8-Max-0902, a post-training upgrade to Qwen3.8-Max that keeps the same 2.4 trillion parameter architecture and 1 million token context while focusing on coding and long-horizon agent performance. The new variant ranks first overall on Code Arena WebDev with 1,691 points, edg The Qwen3.8-Max-0902 update leads Claude Opus 5 on three coding benchmarks (MLS-Bench-Lite, SWE-Atlas QnA, QwenSWEBench V2) and wins on WorkArena and both published multimodal evaluations, though Claude retains leads on TerminalBench 3.0, DeepSWE 1.1, and several agent coordination benchmarks. Additional strong gains a

Merge Gateway

CoverageBenchmark

A third-party benchmark breakdown of Qwen3.8-Max published August 14, 2026 details the model's published scores: PaperBench 93.0, IFBench 82.8, Terminal Bench 2.1 at 86.6, MathVision 95.2, and OSWorld-Verified 86.1, alongside reported losses at HLE 43.6 (last among the four flagships compared) and SWE-bench Pro 67.7 (r The same piece provides context on reported pricing of $2 input and $6 output per million tokens (roughly a third of Claude Opus 5 and a quarter of GPT-5.6 Sol) and comparative framing against Kimi K3, Fable 5, and GPT-5.6 Sol, recommending the benchmark table be treated as a strong vendor claim rather than an independ

Merge Gateway

CoverageBenchmark

Roboflow's evaluation of Qwen3.8-Max for vision tasks confirms the model accepts text, images, and video as input and returns text, available through the Alibaba Cloud API and testable in Roboflow Playground. The model delivered the strongest object detection results in Roboflow's upcoming VLM benchmark, performing wel The vision workflow requires prompting the model to return a JSON list containing a label and four coordinates per detected object, which Roboflow then parses and converts into bounding boxes, with Qwen models working best on XYXY coordinates normalized to a range of 0 to 1000. Open weights were scheduled for release o

Merge Gateway

Coverage

Alibaba officially announced Qwen3.8-Max on August 3, 2026, describing it as the most powerful model in its Qwen series to date. The model is a multimodal foundation built on a Qwen 3.5 base with a Sparse Mixture-of-Experts architecture and hybrid attention mechanism, totaling 2.4 trillion parameters with 95 billion ac The creator-attributed announcement confirms Qwen3.8-Max natively supports visual intelligence and is positioned as Alibaba's flagship, with availability also through QwenWork, Alibaba's all-in-one workplace AI agent platform. Ranked fourth on Fronted Code Arena, the model is designed for autonomous coding and long-hor

Merge Gateway

Coverage

Qwen officially released Qwen3.8-Max, a 2.4-trillion-parameter Mixture-of-Experts model with 95 billion active parameters built on the architectural foundation of Qwen 3.5, marking the first time weights of a Qwen-Max-class model will be open-sourced (releasing the week following the announcement). The post, republishe The announcement positions Qwen3.8-Max against Opus 4.8, Fable 5, GPT-5.6 Sol, and Gemini 3.1 Pro with full benchmark tables, covering coding, RL infrastructure gains, and multimodal agent capabilities. The release emphasizes end-to-end, dependable delivery of complex tasks rather than single-turn response quality, and

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