Model comparison
DeepSeek V4 Pro vs MiMo-V2.5-Pro
Head-to-head evidence from 7 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); MiMo-V2.5-Pro #14 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and MiMo-V2.5-Pro share 7 comparable benchmark results. 3 of 8 categories are comparable. 16 results are unique to DeepSeek V4 Pro; 24 to MiMo-V2.5-Pro.
Updated July 23, 2026- Shared results
- 7
- DeepSeek V4 Pro only
- 16
- MiMo-V2.5-Pro only
- 24
- Comparable categories
- 3 / 8
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro 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 4 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-Pro is clearly ahead on the BenchAlign aggregate, 70.19 to 60.66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5-Pro's sharpest advantage is in agentic, where it averages 68.4 against 59.1. The single biggest benchmark swing on the page is HLE, 7.7% to 48%. DeepSeek V4 Pro does hit back in coding, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5-Pro is the reasoning model in the pair, while DeepSeek V4 Pro 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.
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 | Δ | MiMo-V2.5-Pro |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro59.1 | Margin→ 9.3 | MiMo-V2.5-Pro68.4 |
| Coding | DeepSeek V4 Pro65.3 | Margin← 8.1 | MiMo-V2.5-Pro57.2 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 6.7 | MiMo-V2.5-Pro48.0 |
| Math | DeepSeek V4 Pro31.7 | MarginNo overlap | MiMo-V2.5-ProNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 7.7%B 48%Winner: MiMo-V2.5-ProΔ 40.3HLE: DeepSeek V4 Pro scored 7.7%; MiMo-V2.5-Pro scored 48%. MiMo-V2.5-Pro wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59.1%B 68.4%Winner: MiMo-V2.5-ProΔ 9.3Terminal-Bench 2.0: DeepSeek V4 Pro scored 59.1%; MiMo-V2.5-Pro scored 68.4%. MiMo-V2.5-Pro wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.1%B 57.2%Winner: MiMo-V2.5-ProΔ 5.1SWE-bench Pro: DeepSeek V4 Pro scored 52.1%; MiMo-V2.5-Pro scored 57.2%. MiMo-V2.5-Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | MiMo-V2.5-Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | MiMo-V2.5-ProNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | MiMo-V2.5-ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | MiMo-V2.5-ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | MiMo-V2.5-Pro1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticMiMo-V2.5-Pro wins17 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | 68.4% | MiMo-V2.5-Pro leads |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | 63.8% | MiMo-V2.5-Pro leads |
| Gert LabsSource | 50.28% | 62.70% | MiMo-V2.5-Pro leads |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| GDPval-AASource | — | 1265 | Not comparable |
| τ³-bench resultsSource | — | 72.9% | Not comparable |
| AA Agentic IndexSource | — | 29.1% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 38.3% | Not comparable |
| APEX-Agents-AASource | — | 2.4% | Not comparable |
| AA BriefcaseSource | — | 873 | Not comparable |
| AA ITBenchSource | — | 38.2% | Not comparable |
| terminalBenchHardSource | — | 43.2% | Not comparable |
| aaTerminalBench21Source | — | 65.2% | Not comparable |
| AA Harvey LABSource | — | 73.3% | Not comparable |
CodingDeepSeek V4 Pro wins6 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.6% | — | Not comparable |
| SWE-bench ProSource | 52.1% | 57.2% | MiMo-V2.5-Pro leads |
| SWE MultilingualSource | 69.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 59.1% | 68.4% | MiMo-V2.5-Pro leads |
| AA Coding IndexSource | — | 60.2% | Not comparable |
| AA-SciCodeSource | — | 50.2% | Not comparable |
Reasoning4 benchmarks
KnowledgeMiMo-V2.5-Pro wins14 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | — | Not comparable |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | — | Not comparable |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | 48% | MiMo-V2.5-Pro leads |
| HLE w/o toolsSource | — | 34% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 42.2% | Not comparable |
| AA-GPQA DiamondSource | — | 86.6% | Not comparable |
| AA-HLESource | — | 33.8% | Not comparable |
| AA-Omniscience IndexSource | — | 3.6% | Not comparable |
| AA-Omniscience AccuracySource | — | 22.6% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 24.5% | Not comparable |
| AA Openness IndexSource | — | 38.9% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | 1298 | MiMo-V2.5-Pro leads |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 79.9% | Not comparable |
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Pro or MiMo-V2.5-Pro?
MiMo-V2.5-Pro is ahead on BenchLM's BenchAlign leaderboard, 70.19 to 60.66. The biggest single separator in this matchup is HLE, where the scores are 7.7% and 48%.
Which is better for knowledge tasks, DeepSeek V4 Pro or MiMo-V2.5-Pro?
MiMo-V2.5-Pro has the edge for knowledge tasks in this comparison, averaging 48 versus 41.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro or MiMo-V2.5-Pro?
DeepSeek V4 Pro has the edge for coding in this comparison, averaging 65.3 versus 57.2. 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 or MiMo-V2.5-Pro?
MiMo-V2.5-Pro has the edge for agentic tasks in this comparison, averaging 68.4 versus 59.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
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