DeepSeek-V4-Pro vs Qwen3.7-Max
Direct spec comparison of DeepSeek-V4-Pro (from DeepSeek) and Qwen3.7-Max (from Alibaba). Want a 3- or 4-way comparison? Open the multi-model tool →
 DeepSeek-V4-ProDeepSeek |  Qwen3.7-MaxAlibaba | |
|---|---|---|
| Vendor | DeepSeek | Alibaba |
| Family | DeepSeek | Qwen |
| Release date | 2026-04-22 | 2026-05-20 |
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Parameters | 1.6T (49B active) | — |
| Modality | text | text |
| License | MIT | proprietary |
| Source | open weights | proprietary |
| Description | DeepSeek's flagship open-weight MoE. 1.6T parameters with 49B activated, 1M-token context, and a hybrid attention scheme (CSA + HCA) that delivers long-context inference at ~27% of V3.2's FLOPs. | Alibaba's flagship agent model — 1M-token context, extended-thinking mode, 56.6 on the Artificial Analysis Intelligence Index v4.0 (5th overall, #1 Chinese). 50.8% on Terminal-Bench Hard. Designed for long-horizon agent workloads (hundreds-to-thousands of steps). Closed-weight, $2.50/$7.50 per 1M tokens. |
| Links | ||
| Benchmarks | ||
| MMLU-Pro | 84.2% | 83.7% |
| GPQA-D | 82.4% | 83.0% |
| HumanEval | 95.1% | 93.9% |
| Aider | 80.1% | 78.4% |
| AIME-25 | 88.6% | 90.4% |
| LiveCB | 72.4% | 71.0% |
More like this
Looking for a different head-to-head? Build your own comparison on the multi-model tool.
Or see all DeepSeek-V4-Pro details / Qwen3.7-Max details.