# DeepSeek-V3.2-Speciale vs Gemini 1.5 Flash (May 2024)

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 32.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-gemini-1-5-flash
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 2 categories and Gemini 1.5 Flash (May 2024) in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 20.8.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 24.9% for Gemini 1.5 Flash (May 2024).
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 39.1 | 32.9 |
| Rank | 159 | 240 |
| Context | 128K | — |
| Input $/M | $0.58 | — |
| Output $/M | $1.68 | — |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- Gemini 1.5 Flash (May 2024): 33.9 (#233)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| WeirdML | 46.7% | 24.9% |
| BigCodeBench Instruct | — | 43.5% |
| LMArena Coding | — | 1262 |
| BigCodeBench Complete | — | 55.1% |
| HumanEval+ | — | 75.6% |
| MBPP+ | — | 67.5% |

## Agentic & Tool Use

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 26.3 (#97)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| BALROG | — | 14.6% |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- Gemini 1.5 Flash (May 2024): 20.8 (#212)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1257 |
| DTBench | — | 53.8% |
| Epoch Capabilities Index | — | 129.37 |
| ForecastBench | — | 53.9 |
| PIQA | — | 87.5% |

## Math

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 20.8 (#274)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 16.3% |
| Omni-MATH | — | 30.4% |
| LMArena Math | — | 1269 |
| MATH Level 5 | — | 61.9% |
| FrontierMath (Feb 2025 set) | — | 0% |
| GSM8K | — | 82.4% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 26.2 (#253)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| GPQA Diamond | — | 47.3% |
| MMLU-Pro | — | 67.8% |
| GPQA (HELM) | — | 43.7% |
| LMArena Expert | — | 1233 |
| BoolQ | — | 85.8% |
| MMLU | — | 77.9% |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 35.3 (#76)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| LMArena Vision | — | 1141 |
| Video-MME | — | 70.3% |
| GeoBench | — | 76% |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 43.1 (#184)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| LMArena Non-English | — | 1278 |
| LMArena Chinese | — | 1295 |
| LMArena French | — | 1257 |
| LMArena German | — | 1262 |
| LMArena Japanese | — | 1252 |
| LMArena Korean | — | 1220 |
| LMArena Russian | — | 1288 |
| LMArena Spanish | — | 1242 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 67.0 (#199)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| IFEval | — | 83.1% |
| LMArena Instruction Following | — | 1258 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Gemini 1.5 Flash (May 2024): 39.0 (#182)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| LMArena Longer Query | — | 1284 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- Gemini 1.5 Flash (May 2024): 48.9 (#190)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash (May 2024) |
|---|---|---|
| LMArena Text | — | 1287 |
| LMArena Creative Writing | — | 1285 |
| EQ-Bench Creative Writing | 1276 | — |
| WildBench | — | 79.2% |
| LMArena Multi-Turn | — | 1253 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Gemini 1.5 Flash (May 2024)?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 32.9 on the Noometry Index.

### Is DeepSeek-V3.2-Speciale or Gemini 1.5 Flash (May 2024) better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 33.9 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 1.5 Flash (May 2024) share?

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 1.5 Flash (May 2024) has 42.