Model comparison
Claude Opus 4.7 (Adaptive) vs MiMo-V2-Pro
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); MiMo-V2-Pro #17 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and MiMo-V2-Pro share 12 comparable benchmark results. 1 of 8 categories are comparable. 26 results are unique to Claude Opus 4.7 (Adaptive); 3 to MiMo-V2-Pro.
Updated July 23, 2026- Shared results
- 12
- Claude Opus 4.7 (Adaptive) only
- 26
- MiMo-V2-Pro only
- 3
- Comparable categories
- 1 / 8
Pick MiMo-V2-Pro if you want the stronger benchmark profile. Claude Opus 4.7 (Adaptive) only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 evidence categories; 1 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-Pro has the cleaner BenchAlign overall profile here, landing at 67.78 versus 66.27. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
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 | Claude Opus 4.7 (Adaptive) | Δ | MiMo-V2-Pro |
|---|---|---|---|
| Coding | Claude Opus 4.7 (Adaptive)78.6 | Margin← 0.6 | MiMo-V2-Pro78.0 |
| Agentic | Claude Opus 4.7 (Adaptive)75.1 | MarginNo overlap | MiMo-V2-ProNot measured |
| Reasoning | Claude Opus 4.7 (Adaptive)75.8 | MarginNo overlap | MiMo-V2-ProNot measured |
| Knowledge | Claude Opus 4.7 (Adaptive)60.0 | MarginNo overlap | MiMo-V2-ProNot measured |
| Multimodal | Claude Opus 4.7 (Adaptive)65.1 | MarginNo overlap | MiMo-V2-ProNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 87.6%B 78%Winner: Claude Opus 4.7 (Adaptive)Δ 9.6SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; MiMo-V2-Pro scored 78%. Claude Opus 4.7 (Adaptive) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | MiMo-V2-ProNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | MiMo-V2-ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | MiMo-V2-ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | MiMo-V2-Pro1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.4% | — | Not comparable |
| BrowseCompSource | 79.3% | — | Not comparable |
| MCP AtlasSource | 77.3% | — | Not comparable |
| OSWorld-VerifiedSource | 78% | — | Not comparable |
| CyberGymSource | 73.1% | — | Not comparable |
| AA Agentic IndexSource | 44.4% | — | Not comparable |
| τ²-bench resultsSource | 88.6% | 95% | MiMo-V2-Pro leads |
| GDPval-AASource | 49.8% | — | Not comparable |
| GDPval-AASource | 1495 | — | Not comparable |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
| Claw-EvalSource | — | 57.8% | Not comparable |
| Gert LabsSource | — | 36.68% | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
CodingClaude Opus 4.7 (Adaptive) wins5 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 87.6% | 78% | Claude Opus 4.7 (Adaptive) leads |
| SWE-bench ProSource | 64.3% | — | Not comparable |
| Terminal-Bench 2.0Source | 69.4% | — | Not comparable |
| AA Coding IndexSource | 73.6% | — | Not comparable |
| AA-SciCodeSource | 54.5% | 42.5% | Claude Opus 4.7 (Adaptive) leads |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Result |
|---|---|---|---|
| GPQASource | 94.2% | — | Not comparable |
| GPQA-DSource | 94.2% | — | Not comparable |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 46.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 53.5% | 40.3% | Claude Opus 4.7 (Adaptive) leads |
| AA-GPQA DiamondSource | 91.4% | 87.0% | Claude Opus 4.7 (Adaptive) leads |
| AA-HLESource | 39.6% | 28.3% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience IndexSource | 26.2% | 4.9% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience AccuracySource | 45.8% | 26.8% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience Hallucination RateSource | 36.2% | 29.9% | MiMo-V2-Pro leads |
Math1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 43.8% | — | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | MiMo-V2-Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 58.6% | 68.8% | MiMo-V2-Pro leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 (Adaptive) or MiMo-V2-Pro?
MiMo-V2-Pro is ahead on BenchLM's BenchAlign leaderboard, 67.78 to 66.27. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 87.6% and 78%.
Which is better for coding, Claude Opus 4.7 (Adaptive) or MiMo-V2-Pro?
Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 78. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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