# DeepSeek-V3.2-Speciale vs GPT-4o mini

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 25.4 on the Noometry Index. GPT-4o mini costs 3.3× less per token, which makes it the better buy when DeepSeek-V3.2-Speciale's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-gpt-4o-mini
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and GPT-4o mini in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 8.7.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 10.7% for GPT-4o mini.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.1 | 25.4 |
| Rank | 159 | 337 |
| Context | 128K | 128K |
| Input $/M | $0.58 | $0.15 |
| Output $/M | $1.68 | $0.60 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- GPT-4o mini: 21.6 (#330)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| WeirdML | 46.7% | 11.8% |
| Aider Polyglot | — | 3.6% |
| BigCodeBench Instruct | — | 46.1% |
| LiveBench Coding | — | 43.1% |
| LMArena Coding | — | 1290 |
| BigCodeBench Complete | — | 57.4% |
| HumanEval+ | — | 83.5% |
| MBPP+ | — | 72.2% |

## Agentic & Tool Use

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 27.2 (#95)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| BALROG | — | 17.4% |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- GPT-4o mini: 8.7 (#343)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| SimpleBench | 52.6% | 10.7% |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 28.8% |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | — | 32.8% |
| LMArena Hard Prompts | — | 1267 |
| Mystery Game Puzzles | — | 12% |
| DTBench | — | 54.4% |
| LiveBench Data Analysis | — | 50% |
| LMCA | — | 10.4% |
| Epoch Capabilities Index | — | 126.56 |
| LiveBench | — | 41.3% |
| PIQA | — | 88.7% |

## Math

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 9.9 (#307)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 0.7% |
| OTIS Mock AIME 2024-2025 | — | 6.9% |
| Omni-MATH | — | 28% |
| LiveBench Math | — | 36.3% |
| LMArena Math | — | 1267 |
| MATH Level 5 | — | 52.6% |
| GSM8K | — | 91.3% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 17.7 (#279)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| GPQA Diamond | — | 37.7% |
| SimpleQA Verified | — | 8.3% |
| MMLU-Pro | — | 60.3% |
| Confabulations | — | 37.2% |
| GPQA (HELM) | — | 36.8% |
| LMArena Expert | — | 1235 |
| BoolQ | — | 88.7% |
| MMLU | — | 81.8% |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 25.3 (#117)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| LMArena Vision | — | 1066 |
| Video-MME | — | 64.8% |
| GeoBench | — | 64% |
| VPCT | — | 34% |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 42.2 (#194)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| LMArena Non-English | — | 1266 |
| LMArena Chinese | — | 1264 |
| LMArena French | — | 1296 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1216 |
| LMArena Korean | — | 1195 |
| LMArena Russian | — | 1275 |
| LMArena Spanish | — | 1276 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 62.1 (#234)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| LiveBench Instruction Following | — | 56.8% |
| IFEval | — | 78.2% |
| LMArena Instruction Following | — | 1259 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- GPT-4o mini: 39.1 (#181)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| LMArena Longer Query | — | 1289 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- GPT-4o mini: 39.7 (#243)

| Benchmark | DeepSeek-V3.2-Speciale | GPT-4o mini |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 873 |
| LMArena Text | — | 1286 |
| LMArena Creative Writing | — | 1268 |
| Short-Story Creative Writing | — | 67.2% |
| WildBench | — | 79.1% |
| LMArena Multi-Turn | — | 1285 |
| LiveBench Language | — | 28.6% |

## FAQ

### Is DeepSeek-V3.2-Speciale better than GPT-4o mini?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 25.4 on the Noometry Index. GPT-4o mini costs 3.3× less per token, which makes it the better buy when DeepSeek-V3.2-Speciale's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.2-Speciale or GPT-4o mini?

GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Is DeepSeek-V3.2-Speciale or GPT-4o mini better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 21.6 in the Noometry coding category.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do DeepSeek-V3.2-Speciale and GPT-4o mini share?

3 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and GPT-4o mini has 60.