Model comparison
Deepseek Coder v2 vs GPT-5.2 Pro
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 35.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 34.9.
- Deepseek Coder v2 has downloadable open weights; the other is API-only.
Side by side
| Deepseek Coder v2 | GPT-5.2 Pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 35.9 | 52.3 |
| Released | 2024-06-17 | 2025-12-11 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $21 |
| Output $ / M tokens | — | $168 |
| Results tracked | 24 | 8 |
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Category by category
Coding Not comparable
Deepseek Coder v2: 38.1 (#183), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| BigCodeBench Instruct | 48.2% | — |
| LMArena Coding | 1251 | — |
| BigCodeBench Complete | 59.7% | — |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |
Reasoning GPT-5.2 Pro leads
Deepseek Coder v2: 23.6 (#176), GPT-5.2 Pro: 51.5 (#33)
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| ARC-AGI-2 | — | 54.2% |
| SimpleBench | — | 57.4% |
| NYT Connections (extended) | — | 79.3% |
| ARC-AGI-1 | — | 90.5% |
| LMArena Hard Prompts | 1207 | — |
| Epoch Capabilities Index | — | 155.4 |
| WinoGrande | 83.7% | — |
Math GPT-5.2 Pro leads
Deepseek Coder v2: 34.9 (#190), GPT-5.2 Pro: 65.3 (#29)
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 74% |
| FrontierMath Tier 4 | — | 46% |
| LMArena Math | 1241 | — |
| FrontierMath Tier 4 (v1) | — | 31.3% |
| GSM8K | 94.5% | — |
Knowledge Not comparable
Deepseek Coder v2: 32.3 (#212), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| LMArena Expert | 1181 | — |
| ARC (AI2) Challenge | 64.3% | — |
Multilingual Not comparable
Deepseek Coder v2: 36.3 (#240), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| LMArena Non-English | 1182 | — |
| LMArena Chinese | 1201 | — |
| LMArena French | 1185 | — |
| LMArena German | 1164 | — |
| LMArena Japanese | 1126 | — |
| LMArena Korean | 1104 | — |
| LMArena Russian | 1188 | — |
| LMArena Spanish | 1153 | — |
Instruction Following Not comparable
Deepseek Coder v2: 61.7 (#242), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| LMArena Instruction Following | 1180 | — |
Long Context Not comparable
Deepseek Coder v2: 37.0 (#224), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| LMArena Longer Query | 1219 | — |
Writing & Preference Not comparable
Deepseek Coder v2: 38.2 (#253), GPT-5.2 Pro: —
| Benchmark | Deepseek Coder v2 | GPT-5.2 Pro |
|---|---|---|
| LMArena Text | 1191 | — |
| LMArena Creative Writing | 1120 | — |
| LMArena Multi-Turn | 1177 | — |
Frequently asked questions
Is Deepseek Coder v2 better than GPT-5.2 Pro?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 35.9 on the Noometry Index.
How many benchmarks do Deepseek Coder v2 and GPT-5.2 Pro share?
0 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and GPT-5.2 Pro has 8.