Pricing and context window via OpenRouter, 2026-11-13.
Qwen3.8-27B is a 27B-parameter dense vision-language model built on the Qwen3.5 architecture, improving on Qwen3.6-27B and Qwen3.7-Plus across coding, agentic, and multimodal benchmarks. It adds native image/video understanding, flexible thinking control, and a 262,144-token native context window extensible to 1 million tokens.
Qwen3.8-27B is a 27B dense vision-language model built on the Qwen3.5 architecture, offering native 262K context extensible to 1M tokens and configurable reasoning depth. This release provides FP8-quantized weights for efficient deployment across standard inference frameworks.
| Benchmark | Score | Rank | Source |
|---|---|---|---|
| AA Intelligence Index | 20.1 index | 36 of 47 | Artificial Analysis, Nov 2026 ↗ |
| Arena Elo | 1433 Elo | 73 of 140 | LMArena, Nov 2026 ↗ |
| GPQA | 89.2% | 56 of 162 | Hugging Face model card ↗ |
| Speed (tok/s) | 44 tok/s | 92 of 100 | Artificial Analysis, Nov 2026 ↗ |
Rank is against every model in our database with a sourced score on that benchmark, each counted once with its best score.
Alibaba's Qwen team has released FP8-quantized weights for Qwen3.8-27B, a 27-billion-parameter dense vision-language model with native 262,144-token context extensible to 1 million tokens. The model claims gains over its Qwen3.6 and Qwen3.7 predecessors on coding, agentic, and multimodal benchmarks.
Alibaba's Qwen team has released Qwen3.8-27B, a 27-billion-parameter dense vision-language model with 262,144-token native context extensible to 1 million tokens. The model shows gains over Qwen3.6-27B and Qwen3.7-Plus across coding, agentic, and multimodal benchmarks, according to Alibaba.