# DeepSeek-V2.5 (Sep 2024) vs Gemini 3.8 Flash

> Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 37.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-gemini-3-8-flash
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 0 categories and Gemini 3.8 Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.8 Flash leads 76.9 to 25.6.
- DeepSeek-V2.5 (Sep 2024) has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 37.6 | 61.8 |
| Rank | 200 | 11 |
| Context | — | 1.05M |
| Input $/M | — | $0.75 |
| Output $/M | — | $3.75 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- Gemini 3.8 Flash: 59.2 (#15)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Coding | 1309 | 1510 |
| DeepSWE | — | 73.8% |
| FrontierCode | — | 41.2% |
| Aider Polyglot | 17.8% | — |
| CursorBench | — | 39.6% |
| LMArena WebDev | — | 1584 |
| FrontierSWE | — | 19.6% |
| SciCode | — | 56.6% |
| WeirdML | — | 84.8% |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| ALE-Bench | — | 1,270 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Agentic & Tool Use

- DeepSeek-V2.5 (Sep 2024): —
- Gemini 3.8 Flash: 41.8 (#21)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| APEX-Agents | — | 64.3% |
| Remote Labor Index | — | 5.8% |
| GDP.pdf | — | 23.4% |
| Vending-Bench 2 | — | 5,094 |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)
- Gemini 3.8 Flash: 76.9 (#5)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1508 |
| ARC-AGI-2 | — | 89.2% |
| NYT Connections (extended) | — | 97.4% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 18.3% |
| Chess Puzzles | — | 61% |
| Mystery Game Puzzles | — | 47% |
| DTBench | — | 95.7% |
| LMCA | — | 52.9% |
| Surface Evolver Bench | — | 76.9% |
| Epoch Capabilities Index | — | 156.71 |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- Gemini 3.8 Flash: 65.3 (#28)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Math | 1288 | 1528 |
| FrontierMath (Tiers 1-3) | — | 68.4% |
| FrontierMath Tier 4 | — | 22% |
| OTIS Mock AIME 2024-2025 | — | 98.9% |
| ProofBench | — | 48% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- Gemini 3.8 Flash: 74.8 (#2)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Expert | 1266 | 1524 |
| GPQA Diamond | — | 95.4% |
| Humanity's Last Exam | — | 44.5% |
| SimpleQA Verified | — | 69.7% |

## Multimodal

- DeepSeek-V2.5 (Sep 2024): —
- Gemini 3.8 Flash: 40.7 (#45)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Vision | — | 1314 |
| Blueprint-Bench 2 | — | 38.6% |
| Furniture Assembly | — | 31.7% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- Gemini 3.8 Flash: 58.0 (#5)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Non-English | 1273 | 1491 |
| LMArena Chinese | 1318 | 1554 |
| LMArena French | 1289 | 1498 |
| LMArena German | 1258 | 1493 |
| LMArena Japanese | 1228 | 1502 |
| LMArena Korean | 1209 | 1459 |
| LMArena Russian | 1289 | 1515 |
| LMArena Spanish | 1248 | 1485 |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- Gemini 3.8 Flash: 78.0 (#13)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Instruction Following | 1280 | 1490 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- Gemini 3.8 Flash: 46.3 (#24)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Longer Query | 1301 | 1508 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- Gemini 3.8 Flash: 72.2 (#15)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 3.8 Flash |
|---|---|---|
| LMArena Text | 1294 | 1499 |
| LMArena Creative Writing | 1285 | 1492 |
| LMArena Multi-Turn | 1297 | 1501 |
| EQ-Bench Creative Writing | — | 1748 |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Gemini 3.8 Flash?

Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 37.6 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or Gemini 3.8 Flash better for coding?

Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 31.7 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Gemini 3.8 Flash share?

17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Gemini 3.8 Flash has 50.