Model comparison
MiniMax M3 vs Qwen3.6-27B
Head-to-head evidence from 26 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: MiniMax M3 #18; Qwen3.6-27B #27
BenchAlign evidence: MiniMax M3 supported; Qwen3.6-27B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiniMax M3 and Qwen3.6-27B share 26 comparable benchmark results. 4 of 8 categories are comparable. 19 results are unique to MiniMax M3; 29 to Qwen3.6-27B.
Updated July 16, 2026- Shared results
- 26
- MiniMax M3 only
- 19
- Qwen3.6-27B only
- 29
- Comparable categories
- 4 / 8
Pick MiniMax M3 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiniMax M3 is clearly ahead on the provisional aggregate, 70 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3's sharpest advantage is in agentic, where it averages 72.3 against 59.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 66% to 59.3%. Qwen3.6-27B does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
MiniMax M3 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while MiniMax M3 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. MiniMax M3 gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
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 M3 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Agentic | MiniMax M372.3 | Margin← 13.0 | Qwen3.6-27B59.3 |
| Multimodal | MiniMax M364.9 | Margin→ 11.8 | Qwen3.6-27B76.7 |
| Coding | MiniMax M372.2 | Margin→ 5.3 | Qwen3.6-27B77.5 |
| Math | MiniMax M385.7 | Margin→ 3.5 | Qwen3.6-27B89.2 |
| Knowledge | MiniMax M3Not measured | MarginNo overlap | Qwen3.6-27B53.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 66%B 59.3%Winner: MiniMax M3Δ 6.7Terminal-Bench 2.0: MiniMax M3 scored 66%; Qwen3.6-27B scored 59.3%. MiniMax M3 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 59%B 53.5%Winner: MiniMax M3Δ 5.5SWE-bench Pro: MiniMax M3 scored 59%; Qwen3.6-27B scored 53.5%. MiniMax M3 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80.5%B 77.2%Winner: MiniMax M3Δ 3.3SWE-bench Verified: MiniMax M3 scored 80.5%; Qwen3.6-27B scored 77.2%. MiniMax M3 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 78.1%B 75.8%Winner: MiniMax M3Δ 2.3MMMU-Pro: MiniMax M3 scored 78.1%; Qwen3.6-27B scored 75.8%. MiniMax M3 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M3 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M3$0.3 input / $1.2 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | MiniMax M3Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiniMax M3Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiniMax M31M | Qwen3.6-27B262K | MiniMax M3 lists the larger context window. |
Benchmark Deep Dive
AgenticMiniMax M3 wins20 benchmarks
| Benchmark | MiniMax M3 | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66% | 59.3% | MiniMax M3 leads |
| BrowseCompSource | 83.5% | — | Not comparable |
| OSWorld-VerifiedSource | 70.1% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| Claw-EvalSource | 74.5% | 72.4% | MiniMax M3 leads |
| AA Agentic IndexSource | 35.4% | 27.0% | MiniMax M3 leads |
| τ²-bench resultsSource | 88.9% | 94.2% | Qwen3.6-27B leads |
| GDPval-AASource | 44.7% | 32.0% | MiniMax M3 leads |
| GDPval-AASource | 1395 | 1140 | MiniMax M3 leads |
| GDPval rubricsSource | 74.7% | — | Not comparable |
| BankerToolBenchSource | 76.1% | — | Not comparable |
| ResearchClawBenchSource | 19.8% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| AA BriefcaseSource | 1110 | — | Not comparable |
| AA EnterpriseOps-GymSource | 32.1% | — | Not comparable |
| AA Harvey LABSource | 6.7% | — | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
CodingQwen3.6-27B wins13 benchmarks
| Benchmark | MiniMax M3 | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.5% | 77.2% | MiniMax M3 leads |
| SWE-bench ProSource | 59% | 53.5% | MiniMax M3 leads |
| Terminal-Bench 2.0Source | 66.0% | 59.3% | MiniMax M3 leads |
| NL2RepoSource | 42.1% | 36.2% | MiniMax M3 leads |
| AA Coding IndexSource | 58.6% | 53.7% | MiniMax M3 leads |
| Terminal-Bench HardSource | 42.4% | 34.8% | MiniMax M3 leads |
| AA-SciCodeSource | 45.4% | 39.8% | MiniMax M3 leads |
| VIBE V2Source | 50.1% | — | Not comparable |
| SVG-BenchSource | 63.7% | — | Not comparable |
| KernelBench HardSource | 28.8% | — | Not comparable |
| AA Terminal-Bench 2.1Source | 65.2% | — | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
Reasoning2 benchmarks
Knowledge13 benchmarks
| Benchmark | MiniMax M3 | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.4% | 37.0% | MiniMax M3 leads |
| AA-GPQA DiamondSource | 92.9% | 84.2% | MiniMax M3 leads |
| AA-HLESource | 37.1% | 21.6% | MiniMax M3 leads |
| AA-Omniscience IndexSource | 1.4% | -19.8% | MiniMax M3 leads |
| AA-Omniscience AccuracySource | 15.0% | 19.2% | Qwen3.6-27B leads |
| AA-Omniscience Hallucination RateSource | 16.1% | 48.3% | MiniMax M3 leads |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins6 benchmarks
MultimodalQwen3.6-27B wins19 benchmarks
| Benchmark | MiniMax M3 | Qwen3.6-27B | Result |
|---|---|---|---|
| OfficeQA ProSource | 45.1% | — | Not comparable |
| OmniDocBench 1.5Source | 91.6% | — | Not comparable |
| MMMU-ProSource | 78.1% | 75.8% | MiniMax M3 leads |
| VideoMMMUSource | 84.6% | 84.4% | MiniMax M3 leads |
| Video-MME (with subtitle)Source | 85.4% | 87.7% | Qwen3.6-27B leads |
| Design Arena WebsiteSource | 1294 | — | Not comparable |
| AA-MMMU-ProSource | 78.6% | 74.6% | MiniMax M3 leads |
| MMMUSource | — | 82.9% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MiniMax M3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 82.9% | 67.6% | MiniMax M3 leads |
Frequently Asked Questions (5)
Which is better, MiniMax M3 or Qwen3.6-27B?
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 70 to 66. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 66% and 59.3%.
Which is better for coding, MiniMax M3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 72.2. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Which is better for math, MiniMax M3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 85.7. MiniMax M3 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, MiniMax M3 or Qwen3.6-27B?
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 72.3 versus 59.3. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, MiniMax M3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.7 versus 64.9. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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