Model comparison
DeepSeek-V3.2-Speciale vs o3-mini
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 36.7 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeekSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 1 category and o3-mini in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 16.3.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 22.8% for o3-mini.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $1.10 / $4.40 for o3-mini.
- o3-mini accepts more context: 200K tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | o3-mini | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.7 | 36.7 |
| Released | 2025-12-01 | 2024-12-20 |
| Weights | Open | Proprietary |
| Context window | 128K | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $0.58 | $1.10 |
| Output $ / M tokens | $1.68 | $4.40 |
| Results tracked | 3 | 51 |
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Category by category
Coding Too close to call
DeepSeek-V3.2-Speciale: 40.4 (#140), o3-mini: 40.8 (#132)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| WeirdML | 46.7% | 43.7% |
| Aider Polyglot | — | 60.4% |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| LiveBench Coding | — | 82.7% |
| LMArena Coding | — | 1378 |
| CadEval | — | 54% |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 29.6 (#84)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| Cybench | — | 22.5% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), o3-mini: 16.3 (#305)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| SimpleBench | 52.6% | 22.8% |
| ARC-AGI-2 | — | 3% |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 17% |
| LiveBench Reasoning | — | 89.6% |
| LMArena Hard Prompts | — | 1366 |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LiveBench Data Analysis | — | 70.6% |
| LMCA | — | 19% |
| Epoch Capabilities Index | — | 140.34 |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 28.1 (#244)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 18.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 76.9% |
| LiveBench Math | — | 77.3% |
| LMArena Math | — | 1396 |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 38.3 (#146)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| GPQA Diamond | — | 77% |
| SimpleQA Verified | — | 15.3% |
| Confabulations | — | 17.9% |
| LMArena Expert | — | 1364 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 45.7 (#164)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| LMArena Non-English | — | 1319 |
| LMArena Chinese | — | 1379 |
| LMArena French | — | 1334 |
| LMArena German | — | 1303 |
| LMArena Japanese | — | 1286 |
| LMArena Korean | — | 1314 |
| LMArena Russian | — | 1304 |
| LMArena Spanish | — | 1321 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 75.1 (#72)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| LiveBench Instruction Following | — | 84.4% |
| LMArena Instruction Following | — | 1337 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, o3-mini: 33.8 (#256)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| Fiction.LiveBench | — | 50% |
| LMArena Longer Query | — | 1343 |
Writing & Preference o3-mini leads
DeepSeek-V3.2-Speciale: 46.0 (#222), o3-mini: 50.3 (#182)
| Benchmark | DeepSeek-V3.2-Speciale | o3-mini |
|---|---|---|
| LMArena Text | — | 1337 |
| LMArena Creative Writing | — | 1286 |
| Short-Story Creative Writing | — | 61.7% |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1320 |
| LiveBench Language | — | 50.7% |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than o3-mini?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 36.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or o3-mini?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; o3-mini lists at $1.10 and $4.40.
Is DeepSeek-V3.2-Speciale or o3-mini better for coding?
They score almost the same on coding (40.4 vs 40.8); test both on your own repository before choosing.
Which has the bigger context window?
o3-mini does, with 200K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and o3-mini share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and o3-mini has 51.