# DeepSeek V4 Pro vs MiMo-V2.5

> DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 43.0 on the Noometry Index. MiMo-V2.5 costs 3.1× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v4-pro-vs-mimo-v2-5
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 8 categories and MiMo-V2.5 in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Pro leads 64.6 to 35.4.
- The biggest single-benchmark swing is ProofBench: 50% for DeepSeek V4 Pro and 16% for MiMo-V2.5.
- MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.43 / $0.87 for DeepSeek V4 Pro.
- MiMo-V2.5 accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 54.2 | 43.0 |
| Rank | 28 | 89 |
| Context | 1M | 1.05M |
| Input $/M | $0.43 | $0.14 |
| Output $/M | $0.87 | $0.28 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.2 (#31)
- MiMo-V2.5: 43.6 (#75)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena WebDev | 1582 | 1438 |
| SciCode | 51% | 43.1% |
| LMArena Coding | 1470 | 1469 |
| ALE-Bench | 1,403 | 513.95 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| WeirdML | 66.2% | — |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.7 (#54)
- MiMo-V2.5: —

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.4 (#22)
- MiMo-V2.5: 27.8 (#98)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| CritPt | 18% | 3.7% |
| LMArena Hard Prompts | 1461 | 1450 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| Chess Puzzles | 47% | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.39 | — |
| ForecastBench | 56.1 | — |

## Math

- DeepSeek V4 Pro: 64.6 (#24)
- MiMo-V2.5: 35.4 (#145)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| ProofBench | 50% | 16% |
| LMArena Math | 1455 | 1436 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#28)
- MiMo-V2.5: 40.2 (#109)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Expert | 1463 | 1459 |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |

## Multimodal

- DeepSeek V4 Pro: —
- MiMo-V2.5: 39.0 (#53)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Vision | — | 1245 |

## Multilingual

- DeepSeek V4 Pro: 54.5 (#44)
- MiMo-V2.5: 52.0 (#96)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Non-English | 1438 | 1404 |
| LMArena Chinese | 1486 | 1467 |
| LMArena French | 1473 | 1447 |
| LMArena German | 1458 | 1421 |
| LMArena Japanese | 1448 | 1304 |
| LMArena Korean | 1452 | 1363 |
| LMArena Russian | 1452 | 1395 |
| LMArena Spanish | 1457 | 1412 |

## Instruction Following

- DeepSeek V4 Pro: 76.3 (#44)
- MiMo-V2.5: 75.7 (#55)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1433 |

## Long Context

- DeepSeek V4 Pro: 45.0 (#49)
- MiMo-V2.5: 44.1 (#69)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Longer Query | 1459 | 1444 |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.6 (#45)
- MiMo-V2.5: 61.8 (#82)

| Benchmark | DeepSeek V4 Pro | MiMo-V2.5 |
|---|---|---|
| LMArena Text | 1451 | 1427 |
| LMArena Creative Writing | 1446 | 1392 |
| LMArena Multi-Turn | 1467 | 1445 |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than MiMo-V2.5?

DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 43.0 on the Noometry Index. MiMo-V2.5 costs 3.1× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek V4 Pro or MiMo-V2.5?

MiMo-V2.5 is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; DeepSeek V4 Pro lists at $0.43 and $0.87.

### Is DeepSeek V4 Pro or MiMo-V2.5 better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.2 versus 43.6 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 1M.

### How many benchmarks do DeepSeek V4 Pro and MiMo-V2.5 share?

22 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and MiMo-V2.5 has 23.