Model comparison
DeepSeek-V3.2-Speciale vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 41× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 1 category and o3-pro in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in coding, where o3-pro leads 55.5 to 40.4.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 58.2% for o3-pro.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro 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-pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.7 | 42.9 |
| Released | 2025-12-01 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 128K | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $0.58 | $20 |
| Output $ / M tokens | $1.68 | $80 |
| Results tracked | 3 | 12 |
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Category by category
Coding o3-pro leads
DeepSeek-V3.2-Speciale: 40.4 (#140), o3-pro: 55.5 (#24)
| Benchmark | DeepSeek-V3.2-Speciale | o3-pro |
|---|---|---|
| WeirdML | 46.7% | 58.2% |
| Aider Polyglot | — | 84.9% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), o3-pro: 23.8 (#171)
| Benchmark | DeepSeek-V3.2-Speciale | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, o3-pro: 29.5 (#238)
| Benchmark | DeepSeek-V3.2-Speciale | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, o3-pro: 72.2 (#1)
| Benchmark | DeepSeek-V3.2-Speciale | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
Writing & Preference o3-pro leads
DeepSeek-V3.2-Speciale: 46.0 (#222), o3-pro: 57.1 (#133)
| Benchmark | DeepSeek-V3.2-Speciale | o3-pro |
|---|---|---|
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1276 | — |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 41× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.2-Speciale or o3-pro?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; o3-pro lists at $20 and $80.
Is DeepSeek-V3.2-Speciale or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
o3-pro does, with 200K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and o3-pro share?
1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and o3-pro has 12.