# DeepSeek-V3.2-Speciale vs Gemini 2.5 Flash

> DeepSeek-V3.2-Speciale and Gemini 2.5 Flash score almost the same on the Noometry Index (39.7 vs 39.3), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-gemini-2-5-flash
- Last updated: 2026-10-12
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 2 categories and Gemini 2.5 Flash in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 18.1.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 41.2% for Gemini 2.5 Flash.
- Both cost about the same: $0.58 input and $1.68 output per million tokens.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 39.7 | 39.3 |
| Rank | 162 | 170 |
| Context | 128K | 1.05M |
| Input $/M | $0.58 | $0.30 |
| Output $/M | $1.68 | $2.50 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Speciale: 40.4 (#140)
- Gemini 2.5 Flash: 35.8 (#220)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| WeirdML | 46.7% | 41.9% |
| SWE-bench Verified (bash only) | — | 28.7% |
| Aider Polyglot | — | 55.1% |
| LMArena Coding | — | 1424 |
| ALE-Bench | — | 661.88 |

## Agentic & Tool Use

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 30.8 (#74)

| Benchmark | DeepSeek-V3.2-Speciale | 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-V3.2-Speciale: 32.9 (#73)
- Gemini 2.5 Flash: 18.1 (#286)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| SimpleBench | 52.6% | 41.2% |
| ARC-AGI-2 | — | 2.5% |
| Kagi LLM Benchmark | — | 56.8% |
| ARC-AGI-1 | — | 33.3% |
| CritPt | — | 1.1% |
| EnigmaEval | — | 2.7% |
| LMArena Hard Prompts | — | 1422 |
| DTBench | — | 76.5% |
| LMCA | — | 27.5% |
| Epoch Capabilities Index | — | 143.03 |
| ForecastBench | — | 60.6 |

## Math

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 39.9 (#98)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 73.1% |
| Omni-MATH | — | 38.5% |
| LMArena Math | — | 1415 |
| FrontierMath (Feb 2025 set) | — | 4.8% |
| FrontierMath Tier 4 (v1) | — | 4.2% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 36.4 (#168)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| Humanity's Last Exam | — | 12.1% |
| MMLU-Pro | — | 63.9% |
| Confabulations | — | 16.8% |
| Vectara Hallucination Rate | — | 7.8% |
| GPQA (HELM) | — | 39% |
| LMArena Expert | — | 1426 |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 41.8 (#32)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| LMArena Vision | — | 1253 |
| GeoBench | — | 76% |
| VPCT | — | 46.2% |
| SpatialViz-Bench | — | 36.9% |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 52.3 (#88)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| LMArena Non-English | — | 1409 |
| LMArena Chinese | — | 1450 |
| LMArena French | — | 1433 |
| LMArena German | — | 1418 |
| LMArena Japanese | — | 1405 |
| LMArena Korean | — | 1385 |
| LMArena Russian | — | 1415 |
| LMArena Spanish | — | 1421 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 75.7 (#54)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| IFEval | — | 89.8% |
| LMArena Instruction Following | — | 1405 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Gemini 2.5 Flash: 47.5 (#17)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| Fiction.LiveBench | — | 77.8% |
| LMArena Longer Query | — | 1419 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.0 (#222)
- Gemini 2.5 Flash: 53.8 (#157)

| Benchmark | DeepSeek-V3.2-Speciale | Gemini 2.5 Flash |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1137 |
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1400 |
| Short-Story Creative Writing | — | 76.5% |
| WildBench | — | 81.7% |
| LMArena Multi-Turn | — | 1408 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Gemini 2.5 Flash?

DeepSeek-V3.2-Speciale and Gemini 2.5 Flash score almost the same on the Noometry Index (39.7 vs 39.3), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek-V3.2-Speciale or Gemini 2.5 Flash?

Gemini 2.5 Flash is cheaper. It lists at $0.30 per million input tokens and $2.50 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Is DeepSeek-V3.2-Speciale or Gemini 2.5 Flash better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 35.8 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash does, with 1.05M tokens against 128K.

### How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 2.5 Flash share?

3 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 2.5 Flash has 54.