Model comparison
DeepSeek V4 Pro vs MiMo-V2-Omni
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); MiMo-V2-Omni #40 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and MiMo-V2-Omni share 2 comparable benchmark results. 1 of 8 categories are comparable. 21 results are unique to DeepSeek V4 Pro; 12 to MiMo-V2-Omni.
Updated July 23, 2026- Shared results
- 2
- DeepSeek V4 Pro only
- 21
- MiMo-V2-Omni only
- 12
- Comparable categories
- 1 / 8
Pick MiMo-V2-Omni if you want the stronger benchmark profile. DeepSeek V4 Pro only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 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-Omni has the cleaner BenchAlign overall profile here, landing at 63.15 versus 60.66. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MiMo-V2-Omni's sharpest advantage is in coding, where it averages 74.8 against 65.3. The single biggest benchmark swing on the page is SWE-bench Verified, 73.6% to 74.8%.
MiMo-V2-Omni 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. DeepSeek V4 Pro gives you the larger context window at 1M, compared with 262K for MiMo-V2-Omni.
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-Omni |
|---|---|---|---|
| Coding | DeepSeek V4 Pro65.3 | Margin→ 9.5 | MiMo-V2-Omni74.8 |
| Agentic | DeepSeek V4 Pro59.1 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Knowledge | DeepSeek V4 Pro41.3 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Math | DeepSeek V4 Pro31.7 | MarginNo overlap | MiMo-V2-OmniNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 73.6%B 74.8%Winner: MiMo-V2-OmniΔ 1.2SWE-bench Verified: DeepSeek V4 Pro scored 73.6%; MiMo-V2-Omni scored 74.8%. MiMo-V2-Omni 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-Omni | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | MiMo-V2-OmniNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | MiMo-V2-OmniNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | MiMo-V2-OmniNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | MiMo-V2-Omni262K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2-Omni | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | 45.2% | DeepSeek V4 Pro leads |
| Gert LabsSource | 50.28% | — | Not comparable |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| τ²-bench resultsSource | — | 91.2% | Not comparable |
CodingMiMo-V2-Omni wins5 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2-Omni | 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% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 35.0% | Not comparable |
| AA-GPQA DiamondSource | — | 82.8% | Not comparable |
| AA-HLESource | — | 19.9% | Not comparable |
| AA-Omniscience IndexSource | — | -17.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 18.7% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 44.4% | Not comparable |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | MiMo-V2-Omni | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 53.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Pro or MiMo-V2-Omni?
MiMo-V2-Omni is ahead on BenchLM's BenchAlign leaderboard, 63.15 to 60.66. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.6% and 74.8%.
Which is better for coding, DeepSeek V4 Pro or MiMo-V2-Omni?
MiMo-V2-Omni has the edge for coding in this comparison, averaging 74.8 versus 65.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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