# DeepSeek V4 Pro vs MiMo-V2-Flash

> DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 40.8 on the Noometry Index. MiMo-V2-Flash 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-flash
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 8 categories and MiMo-V2-Flash in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.4 to 24.1.
- The biggest single-benchmark swing is SciCode: 51% for DeepSeek V4 Pro and 25.9% for MiMo-V2-Flash.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.43 / $0.87 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 262K.

## Snapshot

| | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 54.2 | 40.8 |
| Rank | 28 | 137 |
| Context | 1M | 262K |
| Input $/M | $0.43 | $0.14 |
| Output $/M | $0.87 | $0.28 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.2 (#31)
- MiMo-V2-Flash: 35.8 (#205)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena WebDev | 1582 | 1330 |
| SciCode | 51% | 25.9% |
| LMArena Coding | 1470 | 1443 |
| ALE-Bench | 1,403 | 737.95 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| WeirdML | 66.2% | — |

## Agentic & Tool Use

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

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

## Reasoning

- DeepSeek V4 Pro: 56.4 (#22)
- MiMo-V2-Flash: 24.1 (#155)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| CritPt | 18% | 0% |
| LMArena Hard Prompts | 1461 | 1420 |
| 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-Flash: 35.6 (#141)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Math | 1455 | 1396 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#28)
- MiMo-V2-Flash: 39.1 (#126)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Expert | 1463 | 1425 |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |

## Multilingual

- DeepSeek V4 Pro: 54.5 (#44)
- MiMo-V2-Flash: 51.1 (#109)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Non-English | 1438 | 1391 |
| LMArena Chinese | 1486 | 1463 |
| LMArena French | 1473 | 1429 |
| LMArena German | 1458 | 1395 |
| LMArena Japanese | 1448 | 1324 |
| LMArena Korean | 1452 | 1358 |
| LMArena Russian | 1452 | 1387 |
| LMArena Spanish | 1457 | 1420 |

## Instruction Following

- DeepSeek V4 Pro: 76.3 (#44)
- MiMo-V2-Flash: 73.7 (#115)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Instruction Following | 1448 | 1392 |

## Long Context

- DeepSeek V4 Pro: 45.0 (#49)
- MiMo-V2-Flash: 43.0 (#106)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Longer Query | 1459 | 1409 |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.6 (#45)
- MiMo-V2-Flash: 59.9 (#101)

| Benchmark | DeepSeek V4 Pro | MiMo-V2-Flash |
|---|---|---|
| LMArena Text | 1451 | 1411 |
| LMArena Creative Writing | 1446 | 1375 |
| LMArena Multi-Turn | 1467 | 1404 |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than MiMo-V2-Flash?

DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 40.8 on the Noometry Index. MiMo-V2-Flash 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-Flash?

MiMo-V2-Flash 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-Flash better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.2 versus 35.8 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 262K.

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

21 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and MiMo-V2-Flash has 21.