Model comparison
DeepSeek V3.2 vs MiMo-V2.5
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #82 (Supported); MiMo-V2.5 #62 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and MiMo-V2.5 share 3 comparable benchmark results. 1 of 8 categories are comparable. 16 results are unique to DeepSeek V3.2; 8 to MiMo-V2.5.
Updated July 21, 2026- Shared results
- 3
- DeepSeek V3.2 only
- 16
- MiMo-V2.5 only
- 8
- Comparable categories
- 1 / 8
Pick MiMo-V2.5 if you want the stronger benchmark profile. DeepSeek V3.2 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 3 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-V2.5 is clearly ahead on the BenchAlign aggregate, 58.62 to 55.4. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5 is the reasoning model in the pair, while DeepSeek V3.2 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 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.2.
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 V3.2 | Δ | MiMo-V2.5 |
|---|---|---|---|
| Coding | DeepSeek V3.260.9 | Margin← 4.8 | MiMo-V2.556.1 |
| Agentic | DeepSeek V3.2Not measured | MarginNo overlap | MiMo-V2.565.8 |
| Math | DeepSeek V3.217.1 | MarginNo overlap | MiMo-V2.5Not measured |
| Multimodal | DeepSeek V3.2Not measured | MarginNo overlap | MiMo-V2.579.0 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | MiMo-V2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | MiMo-V2.5Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | MiMo-V2.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | MiMo-V2.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | MiMo-V2.51M | MiMo-V2.5 lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | DeepSeek V3.2 | MiMo-V2.5 | Result |
|---|---|---|---|
| Claw-EvalSource | 40.2% | 62.3% | MiMo-V2.5 leads |
| VITA-BenchSource | 18.5% | — | Not comparable |
| τ²-bench resultsSource | 78.9% | — | Not comparable |
| Gert LabsSource | 29.57% | 46.89% | MiMo-V2.5 leads |
| MM-ClawBenchSource | — | 23.8% | Not comparable |
| Terminal-Bench 2.0Source | — | 65.8% | Not comparable |
| ResearchClawBenchSource | — | 16.9% | Not comparable |
CodingDeepSeek V3.2 wins5 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 | MiMo-V2.5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | — | Not comparable |
| AA-GPQA DiamondSource | 75.1% | — | Not comparable |
| AA-HLESource | 10.5% | — | Not comparable |
| AA-Omniscience IndexSource | -46.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 93.5% | — | Not comparable |
Math2 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | MiMo-V2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V3.2 or MiMo-V2.5?
MiMo-V2.5 is ahead on BenchLM's BenchAlign leaderboard, 58.62 to 55.4.
Which is better for coding, DeepSeek V3.2 or MiMo-V2.5?
DeepSeek V3.2 has the edge for coding in this comparison, averaging 60.9 versus 56.1. MiMo-V2.5 stays close enough that the answer can still flip depending on your workload.
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