# Deepseek Coder v2 vs Gemini 2.5 Flash

> Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 35.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-coder-v2-vs-gemini-2-5-flash
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Deepseek Coder v2 scores higher in 2 categories and Gemini 2.5 Flash in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Gemini 2.5 Flash leads 52.3 to 36.3.
- Deepseek Coder v2 has downloadable open weights; the other is API-only.

## Snapshot

| | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 35.9 | 39.3 |
| Rank | 220 | 170 |
| Context | — | 1.05M |
| Input $/M | — | $0.30 |
| Output $/M | — | $2.50 |
| Weights | Open | Proprietary |

## Coding

- Deepseek Coder v2: 38.1 (#183)
- Gemini 2.5 Flash: 35.8 (#220)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Coding | 1251 | 1424 |
| SWE-bench Verified (bash only) | — | 28.7% |
| Aider Polyglot | — | 55.1% |
| WeirdML | — | 41.9% |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 59.7% | — |
| ALE-Bench | — | 661.88 |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |

## Agentic & Tool Use

- Deepseek Coder v2: —
- Gemini 2.5 Flash: 30.8 (#74)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| Terminal-Bench | — | 17.1% |
| Berkeley Function Calling Leaderboard | — | 56.2% |
| TheAgentCompany | — | 41.1% |
| BALROG | — | 33.5% |
| Vending-Bench 2 | — | 548.84 |

## Reasoning

- Deepseek Coder v2: 23.6 (#176)
- Gemini 2.5 Flash: 18.1 (#286)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1422 |
| ARC-AGI-2 | — | 2.5% |
| SimpleBench | — | 41.2% |
| Kagi LLM Benchmark | — | 56.8% |
| ARC-AGI-1 | — | 33.3% |
| CritPt | — | 1.1% |
| EnigmaEval | — | 2.7% |
| DTBench | — | 76.5% |
| LMCA | — | 27.5% |
| Epoch Capabilities Index | — | 143.03 |
| ForecastBench | — | 60.6 |
| WinoGrande | 83.7% | — |

## Math

- Deepseek Coder v2: 34.9 (#190)
- Gemini 2.5 Flash: 39.9 (#98)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Math | 1241 | 1415 |
| OTIS Mock AIME 2024-2025 | — | 73.1% |
| Omni-MATH | — | 38.5% |
| FrontierMath (Feb 2025 set) | — | 4.8% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
| GSM8K | 94.5% | — |

## Knowledge

- Deepseek Coder v2: 32.3 (#212)
- Gemini 2.5 Flash: 36.4 (#168)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Expert | 1181 | 1426 |
| Humanity's Last Exam | — | 12.1% |
| MMLU-Pro | — | 63.9% |
| Confabulations | — | 16.8% |
| Vectara Hallucination Rate | — | 7.8% |
| GPQA (HELM) | — | 39% |
| ARC (AI2) Challenge | 64.3% | — |

## Multimodal

- Deepseek Coder v2: —
- Gemini 2.5 Flash: 41.8 (#32)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Vision | — | 1253 |
| GeoBench | — | 76% |
| VPCT | — | 46.2% |
| SpatialViz-Bench | — | 36.9% |

## Multilingual

- Deepseek Coder v2: 36.3 (#240)
- Gemini 2.5 Flash: 52.3 (#88)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Non-English | 1182 | 1409 |
| LMArena Chinese | 1201 | 1450 |
| LMArena French | 1185 | 1433 |
| LMArena German | 1164 | 1418 |
| LMArena Japanese | 1126 | 1405 |
| LMArena Korean | 1104 | 1385 |
| LMArena Russian | 1188 | 1415 |
| LMArena Spanish | 1153 | 1421 |

## Instruction Following

- Deepseek Coder v2: 61.7 (#242)
- Gemini 2.5 Flash: 75.7 (#54)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Instruction Following | 1180 | 1405 |
| IFEval | — | 89.8% |

## Long Context

- Deepseek Coder v2: 37.0 (#224)
- Gemini 2.5 Flash: 47.5 (#17)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Longer Query | 1219 | 1419 |
| Fiction.LiveBench | — | 77.8% |

## Writing & Preference

- Deepseek Coder v2: 38.2 (#253)
- Gemini 2.5 Flash: 53.8 (#157)

| Benchmark | Deepseek Coder v2 | Gemini 2.5 Flash |
|---|---|---|
| LMArena Text | 1191 | 1417 |
| LMArena Creative Writing | 1120 | 1400 |
| LMArena Multi-Turn | 1177 | 1408 |
| Short-Story Creative Writing | — | 76.5% |
| EQ-Bench Creative Writing | — | 1137 |
| WildBench | — | 81.7% |

## FAQ

### Is Deepseek Coder v2 better than Gemini 2.5 Flash?

Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 35.9 on the Noometry Index.

### Is Deepseek Coder v2 or Gemini 2.5 Flash better for coding?

Deepseek Coder v2 scores higher on coding benchmarks: 38.1 versus 35.8 in the Noometry coding category.

### How many benchmarks do Deepseek Coder v2 and Gemini 2.5 Flash share?

17 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Gemini 2.5 Flash has 54.