Model comparison
DeepSeek V4 Pro (High) 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: DeepSeek V4 Pro (High) #81 (Estimated); MiMo-V2-Pro #17 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and MiMo-V2-Pro share 12 comparable benchmark results. 1 of 8 categories are comparable. 26 results are unique to DeepSeek V4 Pro (High); 3 to MiMo-V2-Pro.
Updated July 23, 2026- Shared results
- 12
- DeepSeek V4 Pro (High) only
- 26
- MiMo-V2-Pro only
- 3
- Comparable categories
- 1 / 8
Pick MiMo-V2-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro (High) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
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 is clearly ahead on the BenchAlign aggregate, 67.78 to 55.47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Pro's sharpest advantage is in coding, where it averages 78 against 69.8. The single biggest benchmark swing on the page is SWE-bench Verified, 79.4% to 78%.
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 | DeepSeek V4 Pro (High) | Δ | MiMo-V2-Pro |
|---|---|---|---|
| Coding | DeepSeek V4 Pro (High)69.8 | Margin→ 8.2 | MiMo-V2-Pro78.0 |
| Agentic | DeepSeek V4 Pro (High)70.6 | MarginNo overlap | MiMo-V2-ProNot measured |
| Knowledge | DeepSeek V4 Pro (High)57.0 | MarginNo overlap | MiMo-V2-ProNot measured |
| Math | DeepSeek V4 Pro (High)94.0 | 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 79.4%B 78%Winner: DeepSeek V4 Pro (High)Δ 1.4SWE-bench Verified: DeepSeek V4 Pro (High) scored 79.4%; MiMo-V2-Pro scored 78%. DeepSeek V4 Pro (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | MiMo-V2-ProNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | MiMo-V2-ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | MiMo-V2-ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | MiMo-V2-Pro1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| BrowseCompSource | 80.4% | — | Not comparable |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| ToolathlonSource | 49% | — | Not comparable |
| τ²-bench resultsSource | 94.2% | 95% | MiMo-V2-Pro leads |
| GDPval-AASource | 39.9% | — | Not comparable |
| GDPval-AASource | 1299 | — | Not comparable |
| AA Agentic IndexSource | 34.4% | — | Not comparable |
| Claw-EvalSource | — | 57.8% | Not comparable |
| Gert LabsSource | — | 36.68% | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
CodingMiMo-V2-Pro wins7 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | 78% | DeepSeek V4 Pro (High) leads |
| SWE-bench ProSource | 54.4% | — | Not comparable |
| SWE MultilingualSource | 74.1% | — | Not comparable |
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| AA-SciCodeSource | 46.4% | 42.5% | DeepSeek V4 Pro (High) leads |
| AA Coding IndexSource | 58.7% | — | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | — | Not comparable |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | — | Not comparable |
| GPQA-DSource | 89.1% | — | Not comparable |
| HLESource | 34.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 43.1% | 40.3% | DeepSeek V4 Pro (High) leads |
| AA-GPQA DiamondSource | 90.5% | 87.0% | DeepSeek V4 Pro (High) leads |
| AA-HLESource | 33.5% | 28.3% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience IndexSource | -9.7% | 4.9% | MiMo-V2-Pro leads |
| AA-Omniscience AccuracySource | 41.8% | 26.8% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 29.9% | MiMo-V2-Pro leads |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2-Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.3% | 68.8% | DeepSeek V4 Pro (High) leads |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Pro (High) or MiMo-V2-Pro?
MiMo-V2-Pro is ahead on BenchLM's BenchAlign leaderboard, 67.78 to 55.47. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 79.4% and 78%.
Which is better for coding, DeepSeek V4 Pro (High) or MiMo-V2-Pro?
MiMo-V2-Pro has the edge for coding in this comparison, averaging 78 versus 69.8. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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