Model comparison
MiMo-V2.5-Pro vs Qwen3.6-27B
Head-to-head evidence from 21 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MiMo-V2.5-Pro #14 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiMo-V2.5-Pro and Qwen3.6-27B share 21 comparable benchmark results. 3 of 8 categories are comparable. 10 results are unique to MiMo-V2.5-Pro; 33 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 21
- MiMo-V2.5-Pro only
- 10
- Qwen3.6-27B only
- 33
- Comparable categories
- 3 / 8
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 5 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiMo-V2.5-Pro is clearly ahead on the BenchAlign aggregate, 70.19 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5-Pro's sharpest advantage is in agentic, where it averages 68.4 against 59.3. The single biggest benchmark swing on the page is HLE, 48% to 24%. Qwen3.6-27B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5-Pro 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 | MiMo-V2.5-Pro | Δ | Qwen3.6-27B |
|---|---|---|---|
| Coding | MiMo-V2.5-Pro57.2 | Margin→ 20.3 | Qwen3.6-27B77.5 |
| Agentic | MiMo-V2.5-Pro68.4 | Margin← 9.1 | Qwen3.6-27B59.3 |
| Knowledge | MiMo-V2.5-Pro48.0 | Margin→ 5.3 | Qwen3.6-27B53.3 |
| Math | MiMo-V2.5-ProNot measured | MarginNo overlap | Qwen3.6-27B89.2 |
| Multimodal | MiMo-V2.5-ProNot measured | MarginNo overlap | Qwen3.6-27B76.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 48%B 24%Winner: MiMo-V2.5-ProΔ 24HLE: MiMo-V2.5-Pro scored 48%; Qwen3.6-27B scored 24%. MiMo-V2.5-Pro wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 68.4%B 59.3%Winner: MiMo-V2.5-ProΔ 9.1Terminal-Bench 2.0: MiMo-V2.5-Pro scored 68.4%; Qwen3.6-27B scored 59.3%. MiMo-V2.5-Pro wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 57.2%B 53.5%Winner: MiMo-V2.5-ProΔ 3.7SWE-bench Pro: MiMo-V2.5-Pro scored 57.2%; Qwen3.6-27B scored 53.5%. MiMo-V2.5-Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiMo-V2.5-Pro | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiMo-V2.5-ProNot available | Qwen3.6-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | MiMo-V2.5-ProNot available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiMo-V2.5-ProNot available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiMo-V2.5-Pro1M | Qwen3.6-27B262K | MiMo-V2.5-Pro lists the larger context window. |
Benchmark Deep Dive
AgenticMiMo-V2.5-Pro wins17 benchmarks
| Benchmark | MiMo-V2.5-Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| Claw-EvalSource | 63.8% | 72.4% | Qwen3.6-27B leads |
| GDPval-AASource | 1265 | 1140 | MiMo-V2.5-Pro leads |
| τ³-bench resultsSource | 72.9% | — | Not comparable |
| Terminal-Bench 2.0Source | 68.4% | 59.3% | MiMo-V2.5-Pro leads |
| AA Agentic IndexSource | 29.1% | 27.0% | MiMo-V2.5-Pro leads |
| τ²-bench resultsSource | 94.2% | 94.2% | Tie |
| GDPval-AASource | 38.3% | 32.0% | MiMo-V2.5-Pro leads |
| APEX-Agents-AASource | 2.4% | — | Not comparable |
| Gert LabsSource | 62.70% | 54.84% | MiMo-V2.5-Pro leads |
| AA BriefcaseSource | 873 | — | Not comparable |
| AA ITBenchSource | 38.2% | — | Not comparable |
| terminalBenchHardSource | 43.2% | — | Not comparable |
| aaTerminalBench21Source | 65.2% | — | Not comparable |
| AA Harvey LABSource | 73.3% | — | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
CodingQwen3.6-27B wins8 benchmarks
| Benchmark | MiMo-V2.5-Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench ProSource | 57.2% | 53.5% | MiMo-V2.5-Pro leads |
| Terminal-Bench 2.0Source | 68.4% | 59.3% | MiMo-V2.5-Pro leads |
| AA Coding IndexSource | 60.2% | 53.7% | MiMo-V2.5-Pro leads |
| AA-SciCodeSource | 50.2% | 39.8% | MiMo-V2.5-Pro leads |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning2 benchmarks
KnowledgeQwen3.6-27B wins14 benchmarks
| Benchmark | MiMo-V2.5-Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| HLESource | 48% | 24% | MiMo-V2.5-Pro leads |
| HLE w/o toolsSource | 34% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | 37.0% | MiMo-V2.5-Pro leads |
| AA-GPQA DiamondSource | 86.6% | 84.2% | MiMo-V2.5-Pro leads |
| AA-HLESource | 33.8% | 21.6% | MiMo-V2.5-Pro leads |
| AA-Omniscience IndexSource | 3.6% | -19.8% | MiMo-V2.5-Pro leads |
| AA-Omniscience AccuracySource | 22.6% | 19.2% | MiMo-V2.5-Pro leads |
| AA-Omniscience Hallucination RateSource | 24.5% | 48.3% | MiMo-V2.5-Pro leads |
| AA Openness IndexSource | 38.9% | — | 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 |
Math5 benchmarks
Multimodal17 benchmarks
| Benchmark | MiMo-V2.5-Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1298 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | 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 |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MiMo-V2.5-Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 79.9% | 67.6% | MiMo-V2.5-Pro leads |
Frequently Asked Questions (4)
Which is better, MiMo-V2.5-Pro or Qwen3.6-27B?
MiMo-V2.5-Pro is ahead on BenchLM's BenchAlign leaderboard, 70.19 to 53.82. The biggest single separator in this matchup is HLE, where the scores are 48% and 24%.
Which is better for knowledge tasks, MiMo-V2.5-Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 53.3 versus 48. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, MiMo-V2.5-Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 57.2. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, MiMo-V2.5-Pro or Qwen3.6-27B?
MiMo-V2.5-Pro has the edge for agentic tasks in this comparison, averaging 68.4 versus 59.3. Inside this category, GDPval-AA 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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