Model comparison
MiniMax M2.7 vs Qwen3.6 Plus
Head-to-head evidence from 23 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MiniMax M2.7 #36 (Supported); Qwen3.6 Plus #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiniMax M2.7 and Qwen3.6 Plus share 23 comparable benchmark results. 2 of 8 categories are comparable. 12 results are unique to MiniMax M2.7; 37 to Qwen3.6 Plus.
Updated July 23, 2026- Shared results
- 23
- MiniMax M2.7 only
- 12
- Qwen3.6 Plus only
- 37
- Comparable categories
- 2 / 8
Pick Qwen3.6 Plus if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6 Plus has the cleaner BenchAlign overall profile here, landing at 65.2 versus 64.11. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6 Plus's sharpest advantage is in coding, where it averages 70.3 against 53.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 57% to 61.6%.
Qwen3.6 Plus is the reasoning model in the pair, while MiniMax M2.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.6 Plus gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | MiniMax M2.7 | Δ | Qwen3.6 Plus |
|---|---|---|---|
| Coding | MiniMax M2.753.3 | Margin→ 17.0 | Qwen3.6 Plus70.3 |
| Agentic | MiniMax M2.757.0 | Margin→ 4.6 | Qwen3.6 Plus61.6 |
| Reasoning | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus62.0 |
| Knowledge | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus57.1 |
| Math | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus60.5 |
| Multilingual | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus84.7 |
| Multimodal | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus79.8 |
| Inst. Following | MiniMax M2.7Not measured | MarginNo overlap | Qwen3.6 Plus82.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 57%B 61.6%Winner: Qwen3.6 PlusΔ 4.6Terminal-Bench 2.0: MiniMax M2.7 scored 57%; Qwen3.6 Plus scored 61.6%. Qwen3.6 Plus wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 56.2%B 56.6%Winner: Qwen3.6 PlusΔ 0.4SWE-bench Pro: MiniMax M2.7 scored 56.2%; Qwen3.6 Plus scored 56.6%. Qwen3.6 Plus wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M2.7 | Qwen3.6 Plus | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M2.7$0.3 input / $1.2 output | Qwen3.6 PlusNot available | A complete price comparison is not available. |
| Generation speedtokens per second | MiniMax M2.745 tok/s | Qwen3.6 PlusNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiniMax M2.72.53 s | Qwen3.6 PlusNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiniMax M2.7200K | Qwen3.6 Plus1M | Qwen3.6 Plus lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.6 Plus wins19 benchmarks
| Benchmark | MiniMax M2.7 | Qwen3.6 Plus | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 57% | 61.6% | Qwen3.6 Plus leads |
| τ²-bench resultsSource | 84.8% | 97.7% | Qwen3.6 Plus leads |
| ToolathlonSource | 46.3% | 39.8% | MiniMax M2.7 leads |
| MLE-Bench LiteSource | 66.6% | — | Not comparable |
| MM-ClawBenchSource | 62.7% | — | Not comparable |
| Claw-EvalSource | 48.7% | 58.8% | Qwen3.6 Plus leads |
| AA Agentic IndexSource | 25.6% | 27.6% | Qwen3.6 Plus leads |
| APEX-Agents-AASource | 10.6% | — | Not comparable |
| GDPval-AASource | 32.9% | 31.8% | MiniMax M2.7 leads |
| GDPval-AASource | 1158 | 1135 | MiniMax M2.7 leads |
| Gert LabsSource | 40.40% | 50.60% | Qwen3.6 Plus leads |
| QwenClawBenchSource | — | 57.2% | Not comparable |
| τ³-bench resultsSource | — | 70.7% | Not comparable |
| VITA-BenchSource | — | 44.3% | Not comparable |
| DeepPlanningSource | — | 41.5% | Not comparable |
| MCP AtlasSource | — | 48.2% | Not comparable |
| MCP-TasksSource | — | 74.1% | Not comparable |
| WideResearchSource | — | 74.3% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
CodingQwen3.6 Plus wins13 benchmarks
| Benchmark | MiniMax M2.7 | Qwen3.6 Plus | Result |
|---|---|---|---|
| SWE-bench Verified*Source | 75.4% | — | Not comparable |
| SWE-bench ProSource | 56.2% | 56.6% | Qwen3.6 Plus leads |
| SWE-RebenchSource | 51.9% | — | Not comparable |
| SWE MultilingualSource | 76.5% | 73.8% | MiniMax M2.7 leads |
| Multi-SWE BenchSource | 52.7% | — | Not comparable |
| VIBE-ProSource | 55.6% | — | Not comparable |
| NL2RepoSource | 39.8% | — | Not comparable |
| Vibe Code BenchSource | 27.04% | 25.56% | MiniMax M2.7 leads |
| React Native EvalsSource | 71.4% | — | Not comparable |
| AA Coding IndexSource | 52.6% | 54.5% | Qwen3.6 Plus leads |
| AA-SciCodeSource | 47.0% | 40.7% | MiniMax M2.7 leads |
| SWE-bench VerifiedSource | — | 78.8% | Not comparable |
| LiveCodeBench v6Source | — | 87.1% | Not comparable |
Reasoning4 benchmarks
Knowledge14 benchmarks
| Benchmark | MiniMax M2.7 | Qwen3.6 Plus | Result |
|---|---|---|---|
| GPQA-DSource | 87.0% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 80.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 38.1% | 39.6% | Qwen3.6 Plus leads |
| AA-GPQA DiamondSource | 87.4% | 88.2% | Qwen3.6 Plus leads |
| AA-HLESource | 28.1% | 25.7% | MiniMax M2.7 leads |
| AA-Omniscience IndexSource | 0.7% | 2.7% | Qwen3.6 Plus leads |
| AA-Omniscience AccuracySource | 26.1% | 26.2% | Qwen3.6 Plus leads |
| AA-Omniscience Hallucination RateSource | 34.4% | 32.0% | Qwen3.6 Plus leads |
| GPQASource | — | 90.4% | Not comparable |
| SuperGPQASource | — | 71.6% | Not comparable |
| MMLU-ProSource | — | 88.5% | Not comparable |
| MMLU-ReduxSource | — | 94.5% | Not comparable |
| C-EvalSource | — | 93.3% | Not comparable |
| HLESource | — | 28.8% | Not comparable |
Math8 benchmarks
| Benchmark | MiniMax M2.7 | Qwen3.6 Plus | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | 80.0% | — | Not comparable |
| AIME26Source | — | 95.3% | Not comparable |
| HMMT Feb 2025Source | — | 96.7% | Not comparable |
| HMMT Nov 2025Source | — | 94.6% | Not comparable |
| HMMT Feb 2026Source | — | 87.8% | Not comparable |
| MMAnswerBenchSource | — | 83.8% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 26.207% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 8.333% | Not comparable |
Multilingual2 benchmarks
Multimodal9 benchmarks
| Benchmark | MiniMax M2.7 | Qwen3.6 Plus | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1275 | 1249 | MiniMax M2.7 leads |
| MMMUSource | — | 86.0% | Not comparable |
| MMMU-ProSource | — | 78.8% | Not comparable |
| MathVisionSource | — | 88.0% | Not comparable |
| VideoMMMUSource | — | 84.0% | Not comparable |
| ScreenSpot ProSource | — | 68.2% | Not comparable |
| CharXivSource | — | 81.5% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 78.0% | Not comparable |
Frequently Asked Questions (3)
Which is better, MiniMax M2.7 or Qwen3.6 Plus?
Qwen3.6 Plus is ahead on BenchLM's BenchAlign leaderboard, 65.2 to 64.11. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 57% and 61.6%.
Which is better for coding, MiniMax M2.7 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for coding in this comparison, averaging 70.3 versus 53.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, MiniMax M2.7 or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for agentic tasks in this comparison, averaging 61.6 versus 57. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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