Qwen 3.8

QwenCloud and Alibaba Cloud Model Studio now list `qwen3.8-max` as a production model rather than a preview-only ID. It accepts image, text, and video input and returns text. QwenCloud documents a 1M-token context window, up to 991K input tokens in non-thinking mode, up to 983K input tokens in thinking mode, a 131K output limit, and up to 262K reasoning tokens.

• Stable request model ID: `qwen3.8-max`.
• QwenCloud price: $2 input, $0.25 implicit-cache input, and $6 output per 1 million tokens.
• Documented API features include function calling, structured output, batches, web search, prompt caching, and fine-tuning.

Qwen publishes the ungated `Qwen/Qwen3.8-27B` checkpoint under Apache 2.0, and QwenCloud lists the stable hosted model ID `qwen3.8-27b`. It is a dense 27B vision-language model with text, image, and video input, text output, 262,144 tokens of native context, and documented extension to 1M tokens. Thinking is enabled by default but can be disabled, and reasoning depth can be set to low, medium, or xhigh.

• QwenCloud price: $0.50 input, $0.10 implicit-cache input, and $3 output per 1 million tokens.
• Hosted limits: 1M context, up to 991K input tokens, 131K output tokens, and 262K reasoning tokens.
• The official model card supports Transformers, vLLM, SGLang, and TokenSpeed; size local hardware from the chosen precision, quantization, context, and concurrency.
• The model card's older hosted-service availability note is superseded by the live QwenCloud model page and callable API example.

Qwen released `Qwen/Qwen3.8-Flash-Next` and an official FP8 checkpoint on August 26, 2026. It is an open multimodal MoE with a 125B-parameter main model, 51B additional n-gram embedding parameters, and 6B parameters activated per token. Qwen presents it as an experimental early look at the architecture planned for Qwen4, not as a completed Qwen4 model.

• Native context is 262,144 tokens and can be extended to 1,000,000 with YaRN; static scaling can reduce short-context quality, so enable it only when needed.
• Text, image, and video inputs produce text output; thinking is enabled by default but can be disabled.
• Official serving paths cover Transformers, llama.cpp, SGLang, vLLM, TokenSpeed, and QwenCloud-compatible APIs.
• Hosted Qwen3.8-Flash is a separate production surface based on Flash-Next with a default 1M context and managed tools; do not transfer hosted limits or prices to the open checkpoint.

Qwen also publishes `Qwen/Qwen3.8-2.4T-A95B` and an official FP8 variant. That sparse model has 2.4T total parameters with 95B activated per token, accepts text only, requires thinking mode, and uses the custom Qwen3.8-Max License. Do not transfer Qwen3.8-27B's Apache license, multimodal input, consumer-hardware fit, or hosted price to the 2.4T checkpoint.

Qwen3.8-27B uses Apache 2.0. The 2.4T checkpoint uses the Qwen3.8-Max License, while Flash-Next uses Qwen Community License 1.0. Both custom licenses broadly permit common model use while adding conditions for specified large commercial products and certain Model-as-a-Service or AI Work Assistant businesses. Read the exact repository license and obtain legal advice for your use case. Infrastructure also differs: the 2.4T checkpoint targets distributed serving, while Flash-Next is smaller but still requires memory planning around precision, quantization, n-gram embedding offload, context, and concurrency.

Qwen publishes favorable coding, agent, general-reasoning, and multimodal results for Qwen3.8-Max, Qwen3.8-27B, and Flash-Next. Treat those tables as vendor-reported. Artificial Analysis provides independent Qwen3.8-27B coverage, while independent Flash-Next evaluation is still early. Compare models on the same prompts, tools, reasoning level, context, latency target, budget, and human-review criteria instead of combining scores from different harnesses.