Model comparison
DeepSeek V4 Pro (High) vs MiMo-V2.5
Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (High) #81 (Estimated); MiMo-V2.5 #62 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and MiMo-V2.5 share 4 comparable benchmark results. 2 of 8 categories are comparable. 34 results are unique to DeepSeek V4 Pro (High); 7 to MiMo-V2.5.
Updated July 23, 2026- Shared results
- 4
- DeepSeek V4 Pro (High) only
- 34
- MiMo-V2.5 only
- 7
- Comparable categories
- 2 / 8
Pick MiMo-V2.5 if you want the stronger benchmark profile. DeepSeek V4 Pro (High) only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 3 evidence categories; 2 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 is clearly ahead on the BenchAlign aggregate, 58.62 to 55.47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
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-V2.5 |
|---|---|---|---|
| Coding | DeepSeek V4 Pro (High)69.8 | Margin← 13.7 | MiMo-V2.556.1 |
| Agentic | DeepSeek V4 Pro (High)70.6 | Margin← 4.8 | MiMo-V2.565.8 |
| Knowledge | DeepSeek V4 Pro (High)57.0 | MarginNo overlap | MiMo-V2.5Not measured |
| Math | DeepSeek V4 Pro (High)94.0 | MarginNo overlap | MiMo-V2.5Not measured |
| Multimodal | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | MiMo-V2.579.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 63.3%B 65.8%Winner: MiMo-V2.5Δ 2.5Terminal-Bench 2.0: DeepSeek V4 Pro (High) scored 63.3%; MiMo-V2.5 scored 65.8%. MiMo-V2.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 54.4%B 56.1%Winner: MiMo-V2.5Δ 1.7SWE-bench Pro: DeepSeek V4 Pro (High) scored 54.4%; MiMo-V2.5 scored 56.1%. MiMo-V2.5 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-V2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | MiMo-V2.5Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | MiMo-V2.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | MiMo-V2.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | MiMo-V2.51M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticDeepSeek V4 Pro (High) wins13 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | 65.8% | MiMo-V2.5 leads |
| 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% | — | Not comparable |
| GDPval-AASource | 39.9% | — | Not comparable |
| GDPval-AASource | 1299 | — | Not comparable |
| AA Agentic IndexSource | 34.4% | — | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| MM-ClawBenchSource | — | 23.8% | Not comparable |
| Gert LabsSource | — | 46.89% | Not comparable |
| ResearchClawBenchSource | — | 16.9% | Not comparable |
CodingDeepSeek V4 Pro (High) wins7 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2.5 | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | — | Not comparable |
| SWE-bench ProSource | 54.4% | 56.1% | MiMo-V2.5 leads |
| SWE MultilingualSource | 74.1% | — | Not comparable |
| Terminal-Bench 2.0Source | 63.3% | 65.8% | MiMo-V2.5 leads |
| AA-SciCodeSource | 46.4% | — | Not comparable |
| AA Coding IndexSource | 58.7% | — | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2.5 | 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% | — | Not comparable |
| AA-GPQA DiamondSource | 90.5% | — | Not comparable |
| AA-HLESource | 33.5% | — | Not comparable |
| AA-Omniscience IndexSource | -9.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 41.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 88.6% | — | Not comparable |
Math4 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | MiMo-V2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.3% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Pro (High) or MiMo-V2.5?
MiMo-V2.5 is ahead on BenchLM's BenchAlign leaderboard, 58.62 to 55.47. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.3% and 65.8%.
Which is better for coding, DeepSeek V4 Pro (High) or MiMo-V2.5?
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 69.8 versus 56.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro (High) or MiMo-V2.5?
DeepSeek V4 Pro (High) has the edge for agentic tasks in this comparison, averaging 70.6 versus 65.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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