Model comparison
DeepSeek-V3.1 vs o3-pro
DeepSeek-V3.1 and o3-pro score almost the same on the Noometry Index (42.8 vs 42.9), so choose on price, context window or the category you care about most.
Last verified . 7 shared benchmarks.
DeepSeekSummary
- They share 7 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 3 categories and o3-pro in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 36.3.
- The biggest single-benchmark swing is Fiction.LiveBench: 52.8% for DeepSeek-V3.1 and 97.2% for o3-pro.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | o3-pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 42.8 | 42.9 |
| Released | 2025-08-21 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 164K | 200K |
| Max output | 8K | 100K |
| Input $ / M tokens | $0.25 | $20 |
| Output $ / M tokens | $0.95 | $80 |
| Results tracked | 27 | 12 |
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Category by category
Coding o3-pro leads
DeepSeek-V3.1: 40.3 (#144), o3-pro: 55.5 (#24)
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| WeirdML | 38.4% | 58.2% |
| Aider Polyglot | — | 84.9% |
| LMArena Coding | 1417 | — |
Reasoning DeepSeek-V3.1 leads
DeepSeek-V3.1: 27.9 (#110), o3-pro: 23.8 (#171)
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 72.1% |
| DTBench | 82.7% | 86.9% |
| LMCA | 24.3% | 38.5% |
| Epoch Capabilities Index | 139.92 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | 40% | — |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 1417 | — |
| ForecastBench | 58 | — |
Math Not comparable
DeepSeek-V3.1: 38.9 (#122), o3-pro: —
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| LMArena Math | 1420 | — |
Knowledge DeepSeek-V3.1 leads
DeepSeek-V3.1: 43.7 (#90), o3-pro: 29.5 (#238)
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | 23.3% |
| Confabulations | — | 14.2% |
| LMArena Expert | 1405 | — |
Multilingual Not comparable
DeepSeek-V3.1: 51.6 (#106), o3-pro: —
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| LMArena Non-English | 1400 | — |
| LMArena Chinese | 1469 | — |
| LMArena French | 1447 | — |
| LMArena German | 1411 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1337 | — |
| LMArena Russian | 1405 | — |
| LMArena Spanish | 1431 | — |
Instruction Following Not comparable
DeepSeek-V3.1: 73.9 (#110), o3-pro: —
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1400 | — |
Long Context o3-pro leads
DeepSeek-V3.1: 36.3 (#232), o3-pro: 72.2 (#1)
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| Fiction.LiveBench | 52.8% | 97.2% |
| LMArena Longer Query | 1422 | — |
Writing & Preference DeepSeek-V3.1 leads
DeepSeek-V3.1: 60.3 (#98), o3-pro: 57.1 (#133)
| Benchmark | DeepSeek-V3.1 | o3-pro |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1401 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1436 | — |
| LMArena Multi-Turn | 1408 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than o3-pro?
DeepSeek-V3.1 and o3-pro score almost the same on the Noometry Index (42.8 vs 42.9), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-V3.1 or o3-pro?
DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; o3-pro lists at $20 and $80.
Is DeepSeek-V3.1 or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 40.3 in the Noometry coding category.
Which has the bigger context window?
o3-pro does, with 200K tokens against 164K.
How many benchmarks do DeepSeek-V3.1 and o3-pro share?
7 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and o3-pro has 12.