Qwen3.7-Max
Editorial notes
Anunciado 19 mayo 2026 en Apsara Summit (Hangzhou). Proprietary agent foundation model (closed-weight). Pricing $2.50/$7.50 per MTok (cache $0.25). Context 1M, output 65K, reasoning nativo (enable_thinking/preserve_thinking). API-only via Alibaba Cloud Model Studio, compatible OpenAI + Anthropic protocols. Solo texto. Lidera GPQA-Diamond (92.4 vs Opus 4.6 91.3) y HLE (41.4 vs Opus 4.6 40.0). Highlight: 35h autonomous kernel optimization (10.0x geometric mean speedup vs Triton ref en hardware T-Head ZW-M890 no visto en training). Otros scores oficiales del blog: HMMT-2026-Feb 97.1, IMOAnswerBench 90.0, Apex 44.5, IFBench 79.1, MRCR-v2 128k 90.4, WMT24++ 85.8, MAXIFE 89.2, PolyMATH 86.5, MMLU-Redux 95.0, SuperGPQA 73.6, MCP-Atlas 76.4, Kernel Bench L3 1.98x/96%.
Spec sheet
- Company
- Alibaba
- Country
- CN
- Type
- reasoning
- Release
- 2026-05
- Context
- 1.0M tokens
- License
- proprietary
- Pricing (alibaba)
- $2.5/$7.5/M
- Slug
- qwen3-7-max
Benchmarks (8)
Reasoning 3
Coding 4
Cite this model
BibTeX · APA
BibTeX
@misc{frontier-qwen3-7-max,
title = {Qwen3.7-Max},
author = {{Alibaba}},
year = {2026},
note = {Frontier Benchmarks AI atlas. Accessed 2026-06-10},
url = {https://frontierbenchmarks.com/models/qwen3-7-max}
} APA
Alibaba (2026). Qwen3.7-Max [Large language model]. Frontier Benchmarks AI. Retrieved 2026-06-10, from https://frontierbenchmarks.com/models/qwen3-7-max
Citation reflects the atlas page, not the original model paper. For the paper, see the "Resources" section above.