See key specs and per-benchmark scores for each model/mode. Scroll horizontally for all columns. 当前对比 2 个模型的评测数据与核心参数。

Qwen 3.6 Plus Preview
阿里巴巴
Each axis is a category average, normalized to a 100-point radar.
Relative edge: 综合评估 +7.6 / Relative gap: 指令跟随 -1.8
Relative edge: 指令跟随 +1.8 / Relative gap: 综合评估 -7.6
Method: for each model and benchmark, the chart first averages all scores in the current mode scope instead of taking the best score, then averages those benchmark scores within each category. Only benchmarks with at least two selected models scored are included; missing values are not counted as zero.
Best overall
Qwen 3.6 Plus Preview · 68.02
Best single
Qwen 3.6 Plus Preview · GPQA Diamond 90.40
Modality coverage
Qwen 3.6 Plus Preview · 0 modalities
Head to head
5
Benchmarks
3
Wins
2
Losses
+4.78
Average diff
Compare benchmark results across thinking modes and tool usage.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Complete scores for each model/mode across selected benchmarks.
5 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | Qwen 3.6 Plus Preview | MiniMax-M2.7 |
|---|---|---|
GPQA Diamond 综合评估 | 90.40Thinking Enabled | 87.00Thinking Enabled |
HLE 综合评估 | 50.60Thinking Enabled | Tools | 28.00Thinking Enabled |
SWE-Bench Pro - Public 编程与软件工程 | 56.60Thinking Enabled | Tools | 56.20Thinking Enabled | Tools |
IF Bench 指令跟随 | 74.20Thinking Enabled | 76.00Thinking Enabled | Tools |
AA-LCR 长上下文能力 | 68.30Thinking Enabled | 69.00Thinking Enabled | Tools |
Side-by-side input/output token pricing
Licensing, MoE architecture, and multi-modality support.
| Features & specs | Qwen 3.6 Plus Preview阿里巴巴 | MiniMax-M2.7MiniMaxAI |
|---|---|---|
Core specsRelease | 2026-03-31 | 2026-03-18 |
Context length | 1M | 200K |
Parameters | — | 2290 |
Active parameters | Not provided | 100 |
Max output | 65536 | 204800 |
MoE | No | Yes |
LicenseCode Open Source | Not provided | Not provided |
Weights Open Source | Not provided | Not provided |
Commercial use | 不开源 | 不可以商用 |
ResourcesPaper / report | Qwen3.6-Plus: Towards Real World Agents | MiniMax M2.7: Early Echoes of Self-Evolution |
DataLearner blog | Not provided | MiniMax M2.7 发布:模型开始帮自己训练自己 |

MiniMax-M2.7
MiniMaxAI