Model comparison
DeepSeek V3 vs MiMo-V2.5-Pro
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3 #147 (Supported); MiMo-V2.5-Pro #14 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3 and MiMo-V2.5-Pro share 16 comparable benchmark results. 2 of 8 categories are comparable. 6 results are unique to DeepSeek V3; 15 to MiMo-V2.5-Pro.
Updated July 21, 2026- Shared results
- 16
- DeepSeek V3 only
- 6
- MiMo-V2.5-Pro only
- 15
- Comparable categories
- 2 / 8
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge 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 16 shared benchmark results across 6 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-Pro is clearly ahead on the BenchAlign aggregate, 70.19 to 44.97. 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 coding, where it averages 57.2 against 38.9. DeepSeek V3 does hit back in knowledge, 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 V3 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. MiMo-V2.5-Pro gives you the larger context window at 1M, compared with 128K for DeepSeek V3.
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 V3 | Δ | MiMo-V2.5-Pro |
|---|---|---|---|
| Knowledge | DeepSeek V372.7 | Margin← 24.7 | MiMo-V2.5-Pro48.0 |
| Coding | DeepSeek V338.9 | Margin→ 18.3 | MiMo-V2.5-Pro57.2 |
| Agentic | DeepSeek V3Not measured | MarginNo overlap | MiMo-V2.5-Pro68.4 |
| Math | DeepSeek V31.7 | MarginNo overlap | MiMo-V2.5-ProNot measured |
| Inst. Following | DeepSeek V386.1 | MarginNo overlap | MiMo-V2.5-ProNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3 | MiMo-V2.5-Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3$0.27 input / $1.1 output | MiMo-V2.5-ProNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3Not available | MiMo-V2.5-ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3Not available | MiMo-V2.5-ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3128K | MiMo-V2.5-Pro1M | MiMo-V2.5-Pro lists the larger context window. |
Benchmark Deep Dive
Agentic14 benchmarks
| Benchmark | DeepSeek V3 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.6% | 29.1% | MiMo-V2.5-Pro leads |
| τ²-bench resultsSource | 22.8% | 94.2% | MiMo-V2.5-Pro leads |
| GDPval-AASource | 0.0% | 38.3% | MiMo-V2.5-Pro leads |
| GDPval-AASource | 217 | 1265 | MiMo-V2.5-Pro leads |
| Claw-EvalSource | — | 63.8% | Not comparable |
| τ³-bench resultsSource | — | 72.9% | Not comparable |
| Terminal-Bench 2.0Source | — | 68.4% | Not comparable |
| APEX-Agents-AASource | — | 2.4% | Not comparable |
| Gert LabsSource | — | 62.70% | 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 |
CodingMiMo-V2.5-Pro wins6 benchmarks
| Benchmark | DeepSeek V3 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| LiveCodeBenchSource | 37.6% | — | Not comparable |
| SWE-bench VerifiedSource | 42% | — | Not comparable |
| AA Coding IndexSource | 23.0% | 60.2% | MiMo-V2.5-Pro leads |
| AA-SciCodeSource | 35.4% | 50.2% | MiMo-V2.5-Pro leads |
| SWE-bench ProSource | — | 57.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 68.4% | Not comparable |
Reasoning2 benchmarks
KnowledgeDeepSeek V3 wins11 benchmarks
| Benchmark | DeepSeek V3 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| GPQASource | 59.1% | — | Not comparable |
| MMLU-ProSource | 75.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.2% | 42.2% | MiMo-V2.5-Pro leads |
| AA-GPQA DiamondSource | 55.7% | 86.6% | MiMo-V2.5-Pro leads |
| AA-HLESource | 3.6% | 33.8% | MiMo-V2.5-Pro leads |
| AA-Omniscience IndexSource | -41.3% | 3.6% | MiMo-V2.5-Pro leads |
| AA-Omniscience AccuracySource | 25.4% | 22.6% | DeepSeek V3 leads |
| AA-Omniscience Hallucination RateSource | 89.4% | 24.5% | MiMo-V2.5-Pro leads |
| HLESource | — | 48% | Not comparable |
| HLE w/o toolsSource | — | 34% | Not comparable |
| AA Openness IndexSource | — | 38.9% | Not comparable |
Math1 benchmarks
| Benchmark | DeepSeek V3 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 1.724% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek V3 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1150 | 1298 | MiMo-V2.5-Pro leads |
Frequently Asked Questions (3)
Which is better, DeepSeek V3 or MiMo-V2.5-Pro?
MiMo-V2.5-Pro is ahead on BenchLM's BenchAlign leaderboard, 70.19 to 44.97.
Which is better for knowledge tasks, DeepSeek V3 or MiMo-V2.5-Pro?
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 72.7 versus 48. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V3 or MiMo-V2.5-Pro?
MiMo-V2.5-Pro has the edge for coding in this comparison, averaging 57.2 versus 38.9. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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