Model comparison
MiMo-V2.5 vs Qwen3.5 397B
Head-to-head evidence from 7 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MiMo-V2.5 #62 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiMo-V2.5 and Qwen3.5 397B share 7 comparable benchmark results. 3 of 8 categories are comparable. 4 results are unique to MiMo-V2.5; 48 to Qwen3.5 397B.
Updated July 21, 2026- Shared results
- 7
- MiMo-V2.5 only
- 4
- Qwen3.5 397B only
- 48
- Comparable categories
- 3 / 8
Pick MiMo-V2.5 if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 3 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 has the cleaner BenchAlign overall profile here, landing at 58.62 versus 57.01. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MiMo-V2.5's sharpest advantage is in agentic, where it averages 65.8 against 56.5. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 65.8% to 52.5%. Qwen3.5 397B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5 is the reasoning model in the pair, while Qwen3.5 397B 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. MiMo-V2.5 gives you the larger context window at 1M, compared with 128K for Qwen3.5 397B.
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 397B |
|---|---|---|---|
| Coding | MiMo-V2.556.1 | Margin→ 10.4 | Qwen3.5 397B66.5 |
| Agentic | MiMo-V2.565.8 | Margin← 9.3 | Qwen3.5 397B56.5 |
| Multimodal | MiMo-V2.579.0 | Margin→ 0.6 | Qwen3.5 397B79.6 |
| Reasoning | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Inst. Following | MiMo-V2.5Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
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 52.5%Winner: MiMo-V2.5Δ 13.3Terminal-Bench 2.0: MiMo-V2.5 scored 65.8%; Qwen3.5 397B scored 52.5%. MiMo-V2.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 56.1%B 50.9%Winner: MiMo-V2.5Δ 5.2SWE-bench Pro: MiMo-V2.5 scored 56.1%; Qwen3.5 397B scored 50.9%. MiMo-V2.5 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 77.9%B 79%Winner: Qwen3.5 397BΔ 1.1MMMU-Pro: MiMo-V2.5 scored 77.9%; Qwen3.5 397B scored 79%. Qwen3.5 397B wins this benchmark. - Source ↗
CharXiv
MultimodalA 81%B 80.8%Winner: MiMo-V2.5Δ 0.2CharXiv: MiMo-V2.5 scored 81%; Qwen3.5 397B scored 80.8%. 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 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiMo-V2.5Not available | Qwen3.5 397B$0.6 input / $3.6 output | A complete price comparison is not available. |
| Generation speedtokens per second | MiMo-V2.5Not available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiMo-V2.5Not available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiMo-V2.51M | Qwen3.5 397B128K | MiMo-V2.5 lists the larger context window. |
Benchmark Deep Dive
AgenticMiMo-V2.5 wins19 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| Claw-EvalSource | 62.3% | 56.8% | MiMo-V2.5 leads |
| MM-ClawBenchSource | 23.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 65.8% | 52.5% | MiMo-V2.5 leads |
| Gert LabsSource | 46.89% | 46.76% | MiMo-V2.5 leads |
| ResearchClawBenchSource | 16.9% | 14.2% | MiMo-V2.5 leads |
| BrowseCompSource | — | 62% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| VITA-BenchSource | — | 43.7% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| AA Agentic IndexSource | — | 19.9% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
| GDPval-AASource | — | 23.1% | Not comparable |
| GDPval-AASource | — | 962 | Not comparable |
CodingQwen3.5 397B wins6 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.7% | Not comparable |
| AA-GPQA DiamondSource | — | 89.3% | Not comparable |
| AA-HLESource | — | 27.3% | Not comparable |
| AA-Omniscience IndexSource | — | -29.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 31.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.1% | Not comparable |
Math5 benchmarks
Multilingual2 benchmarks
MultimodalQwen3.5 397B wins9 benchmarks
| Benchmark | MiMo-V2.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| Video-MME (with subtitle)Source | 87.7% | — | Not comparable |
| CharXivSource | 81% | 80.8% | MiMo-V2.5 leads |
| MMMU-ProSource | 77.9% | 79% | Qwen3.5 397B leads |
| Design Arena WebsiteSource | 1291 | — | Not comparable |
| MathVisionSource | — | 88.6% | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| V*Source | — | 95.8% | Not comparable |
| AA-MMMU-ProSource | — | 77.3% | Not comparable |
Frequently Asked Questions (4)
Which is better, MiMo-V2.5 or Qwen3.5 397B?
MiMo-V2.5 is ahead on BenchLM's BenchAlign leaderboard, 58.62 to 57.01. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 65.8% and 52.5%.
Which is better for coding, MiMo-V2.5 or Qwen3.5 397B?
Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 56.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, MiMo-V2.5 or Qwen3.5 397B?
MiMo-V2.5 has the edge for agentic tasks in this comparison, averaging 65.8 versus 56.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, MiMo-V2.5 or Qwen3.5 397B?
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 79. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.