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Qwen3.8

Qwen3.8
2 min read
Qwen3.8

Qwen3.8, which Alibaba opened on August 12, 2026, is the open-weight release of its Max-class 2.4T-A95B mixture-of-experts, the first Qwen-Max-class model with public weights, joined on August 14 by the dense, Apache 2.0 Qwen3.8-27B.

  • Model: Qwen3.8-2.4T-A95B (Qwen/Qwen3.8-2.4T-A95B) and Qwen3.8-27B (Qwen/Qwen3.8-27B)

  • Maker: Alibaba

  • Ship date: August 12, 2026 (27B on August 14)

  • Pricing: Free (open weights); the 2.4T is hosted as Qwen3.8-Max at $2 / $6 per M tokens

  • Context: 262K tokens native, extendable to about 1M

  • Weights: Open (Qwen3.8-Max License for the 2.4T; Apache 2.0 for the 27B)

  • Where you can use it:

    • Hugging Face and ModelScope weights

    • vLLM, SGLang and TokenSpeed

  • When to reach for it:

    • Self-hosted agentic coding at Max scale

    • The 27B for local runs with image input

    • Skip the 2.4T without a data center

  • How it compares:

    • 2.4T: open peer of Kimi K3 and GLM-5.2

    • 27B: a big step up from Qwen3.6-27B

  • What makes it different:

    • First open Qwen at Max scale, 95B active

    • 2.4T is text-only and always thinks

  • Early reactions: Coverage focused on the license split, with the 27B welcomed as the practical Apache 2.0 pick and the flagship's revenue-capped license drawing skepticism.

  • Read more: Qwen3.8-Max: A New Bar for Coding and Cowork, 2.4T-A95B model card, 27B model card

The benchmarks

The 2.4T always runs in thinking mode (reasoning effort defaults to xhigh) and the 27B thinks by default. The 2.4T card reprints the Qwen3.8-Max launch table, so only two of its rows appear here (the rest are on the Qwen3.8-Max page): Alibaba's own runs in the Claude Code harness against Claude Opus 4.8, Fable 5 (results "may involve fallbacks") and GPT-5.6 Sol at max. The 27B is compared with Qwen3.6-27B, Qwen3.7-Plus, Muse Glimmer-30B and Claude Opus 4.6 at max, using the Terminus harness for Terminal-Bench 2.1 and a corrected SWE-bench Pro task set.

Alibaba's numbers

  • SWE-bench Pro (2.4T-A95B, hard real-repo fixes): 67.7%. −1.5 under Claude Opus 4.8 (69.2%), −12.3 under Fable 5 (80.0%), +3.1 over GPT-5.6 Sol (64.6%).

  • Humanity's Last Exam (no tools) (2.4T-A95B, expert questions): 43.6%. −2.1 under Claude Opus 4.8 (45.7%), −9.7 under Fable 5 (53.3%), −3.6 under GPT-5.6 Sol (47.2%).

  • SWE-bench Pro (27B, hard real-repo fixes): 61.7%. +8.2 over Qwen3.6-27B (53.5%), +4.1 over Qwen3.7-Plus (57.6%), +10.5 over Muse Glimmer-30B (51.2%), +8.3 over Claude Opus 4.6 (53.4%).

  • Terminal-Bench 2.1 (27B, agentic terminal tasks): 73.0%. +9.6 over Qwen3.6-27B (63.4%), +9.0 over Qwen3.7-Plus (64.0%), +21.3 over Muse Glimmer-30B (51.7%), −5.2 under Claude Opus 4.6 (78.2%).

  • GPQA Diamond (27B, PhD-level science): 89.2%. +1.4 over Qwen3.6-27B (87.8%), −1.1 under Qwen3.7-Plus (90.3%), +5.7 over Muse Glimmer-30B (83.5%), −2.1 under Claude Opus 4.6 (91.3%).

  • OSWorld-Verified (27B, computer use): 84.3%. +20.4 over Qwen3.6-27B (63.9%), +11.0 over Qwen3.7-Plus (73.3%), +18.4 over Muse Glimmer-30B (65.9%), +11.6 over Claude Opus 4.6 (72.7%).

Independent numbers

  • Artificial Analysis Intelligence Index (current v4.3.2, 2.4T-A95B): 39.9. −3.7 under Kimi K3 (43.6), +6.2 over GLM-5.2 (33.7), +9.5 over DeepSeek V4 Pro (30.4), +14.9 over Inkling (25.0).

  • Artificial Analysis Intelligence Index (current v4.3.2, 27B): 33.7. +12.3 over Qwen3.6-27B (21.4), +16.2 over Muse Glimmer-30B (17.5).

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