Model comparison
MiMo-V2.5 vs Qwen3.5-27B
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MiMo-V2.5 #62 (Estimated); Qwen3.5-27B #45 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiMo-V2.5 and Qwen3.5-27B share 2 comparable benchmark results. 2 of 8 categories are comparable. 9 results are unique to MiMo-V2.5; 26 to Qwen3.5-27B.
Updated July 21, 2026- Shared results
- 2
- MiMo-V2.5 only
- 9
- Qwen3.5-27B only
- 26
- Comparable categories
- 2 / 8
Pick Qwen3.5-27B if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if agentic is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.5-27B has the cleaner BenchAlign overall profile here, landing at 60.7 versus 58.62. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5-27B's sharpest advantage is in coding, where it averages 64.9 against 56.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 65.8% to 41.6%. MiMo-V2.5 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5 gives you the larger context window at 1M, compared with 262K for Qwen3.5-27B.
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 | Δ | Qwen3.5-27B |
|---|---|---|---|
| Agentic | MiMo-V2.565.8 | Margin← 13.8 | Qwen3.5-27B52.0 |
| Coding | MiMo-V2.556.1 | Margin→ 8.8 | Qwen3.5-27B64.9 |
| Reasoning | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5-27B60.6 |
| Knowledge | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5-27B82.7 |
| Multilingual | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5-27B82.2 |
| Multimodal | MiMo-V2.579.0 | MarginNo overlap | Qwen3.5-27BNot measured |
| Inst. Following | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5-27B95.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 65.8%B 41.6%Winner: MiMo-V2.5Δ 24.2Terminal-Bench 2.0: MiMo-V2.5 scored 65.8%; Qwen3.5-27B scored 41.6%. MiMo-V2.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiMo-V2.5 | Qwen3.5-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiMo-V2.5Not available | Qwen3.5-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | MiMo-V2.5Not available | Qwen3.5-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiMo-V2.5Not available | Qwen3.5-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiMo-V2.51M | Qwen3.5-27B262K | MiMo-V2.5 lists the larger context window. |
Benchmark Deep Dive
AgenticMiMo-V2.5 wins8 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5-27B | Result |
|---|---|---|---|
| Claw-EvalSource | 62.3% | — | Not comparable |
| MM-ClawBenchSource | 23.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 65.8% | 41.6% | MiMo-V2.5 leads |
| Gert LabsSource | 46.89% | 39.41% | MiMo-V2.5 leads |
| ResearchClawBenchSource | 16.9% | — | Not comparable |
| BrowseCompSource | — | 61% | Not comparable |
| OSWorld-VerifiedSource | — | 56.2% | Not comparable |
| τ²-bench resultsSource | — | 93.9% | Not comparable |
CodingQwen3.5-27B wins5 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5-27B | Result |
|---|---|---|---|
| MMLU-ProSource | — | 86.1% | Not comparable |
| SuperGPQASource | — | 65.6% | Not comparable |
| GPQASource | — | 85.5% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.8% | Not comparable |
| AA-GPQA DiamondSource | — | 85.8% | Not comparable |
| AA-HLESource | — | 22.2% | Not comparable |
| AA-Omniscience IndexSource | — | -42.0% | Not comparable |
| AA-Omniscience AccuracySource | — | 21.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 79.7% | Not comparable |
Multilingual1 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5-27B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
Multimodal9 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5-27B | Result |
|---|---|---|---|
| Video-MME (with subtitle)Source | 87.7% | — | Not comparable |
| CharXivSource | 81% | — | Not comparable |
| MMMU-ProSource | 77.9% | — | Not comparable |
| Design Arena WebsiteSource | 1291 | — | Not comparable |
| MMMUSource | — | 82.3% | Not comparable |
| MMVUSource | — | 73.3% | Not comparable |
| MathVisionSource | — | 86.0% | Not comparable |
| V*Source | — | 93.7% | Not comparable |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Frequently Asked Questions (3)
Which is better, MiMo-V2.5 or Qwen3.5-27B?
Qwen3.5-27B is ahead on BenchLM's BenchAlign leaderboard, 60.7 to 58.62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 65.8% and 41.6%.
Which is better for coding, MiMo-V2.5 or Qwen3.5-27B?
Qwen3.5-27B has the edge for coding in this comparison, averaging 64.9 versus 56.1. MiMo-V2.5 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, MiMo-V2.5 or Qwen3.5-27B?
MiMo-V2.5 has the edge for agentic tasks in this comparison, averaging 65.8 versus 52. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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