Model comparison
DeepSeek-V3.1 vs GPT-5.5 Pro
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 42.2 on the Noometry Index. DeepSeek-V3.1 costs 159× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
DeepSeekSummary
- They share 4 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 0 categories and GPT-5.5 Pro in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 Pro leads 83.8 to 36.1.
- The biggest single-benchmark swing is SimpleBench: 40% for DeepSeek-V3.1 and 76.9% for GPT-5.5 Pro.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
- GPT-5.5 Pro accepts more context: 1.05M tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | GPT-5.5 Pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 42.2 | 64.3 |
| Released | 2025-08-21 | 2026-04-23 |
| Weights | Open | Proprietary |
| Context window | 164K | 1.05M |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.25 | $30 |
| Output $ / M tokens | $0.95 | $180 |
| Results tracked | 27 | 14 |
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Category by category
Coding Not comparable
DeepSeek-V3.1: 39.8 (#140), GPT-5.5 Pro: —
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| WeirdML | 38.4% | — |
| LMArena Coding | 1417 | — |
Reasoning GPT-5.5 Pro leads
DeepSeek-V3.1: 27.3 (#109), GPT-5.5 Pro: 73.6 (#7)
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| SimpleBench | 40% | 76.9% |
| DTBench | 82.7% | 96% |
| LMCA | 24.3% | 53.9% |
| Epoch Capabilities Index | 139.92 | 162.45 |
| ARC-AGI-2 | — | 84.6% |
| Kagi LLM Benchmark | 53.2% | — |
| ARC-AGI-1 | — | 96.5% |
| CritPt | — | 30.6% |
| Chess Puzzles | — | 64% |
| LMArena Hard Prompts | 1417 | — |
| ForecastBench | 58 | — |
Math GPT-5.5 Pro leads
DeepSeek-V3.1: 36.1 (#125), GPT-5.5 Pro: 83.8 (#8)
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 87.7% |
| FrontierMath Tier 4 | — | 78% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| LMArena Math | 1420 | — |
| FrontierMath (Feb 2025 set) | — | 52.4% |
| FrontierMath Tier 4 (v1) | — | 39.6% |
Knowledge GPT-5.5 Pro leads
DeepSeek-V3.1: 43.0 (#86), GPT-5.5 Pro: 64.2 (#17)
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| GPQA Diamond | — | 93.9% |
| Vectara Hallucination Rate | 5.5% | — |
| LMArena Expert | 1403 | — |
Multilingual Not comparable
DeepSeek-V3.1: 51.8 (#100), GPT-5.5 Pro: —
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| LMArena Non-English | 1400 | — |
| LMArena Chinese | 1470 | — |
| LMArena French | 1447 | — |
| LMArena German | 1412 | — |
| LMArena Japanese | 1374 | — |
| LMArena Korean | 1337 | — |
| LMArena Russian | 1405 | — |
| LMArena Spanish | 1429 | — |
Instruction Following Not comparable
DeepSeek-V3.1: 74.1 (#105), GPT-5.5 Pro: —
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| LMArena Instruction Following | 1400 | — |
Long Context Not comparable
DeepSeek-V3.1: 36.3 (#227), GPT-5.5 Pro: —
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| Fiction.LiveBench | 52.8% | — |
| LMArena Longer Query | 1422 | — |
Writing & Preference Not comparable
DeepSeek-V3.1: 60.5 (#93), GPT-5.5 Pro: —
| Benchmark | DeepSeek-V3.1 | GPT-5.5 Pro |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1436 | — |
| LMArena Multi-Turn | 1408 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than GPT-5.5 Pro?
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 42.2 on the Noometry Index. DeepSeek-V3.1 costs 159× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1 or GPT-5.5 Pro?
DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.5 Pro lists at $30 and $180.
Which has the bigger context window?
GPT-5.5 Pro does, with 1.05M tokens against 164K.
How many benchmarks do DeepSeek-V3.1 and GPT-5.5 Pro share?
4 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.5 Pro has 14.