Model comparison
DeepSeek-V3.2-Speciale vs GPT-4
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.1 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 3 categories and GPT-4 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 17.8.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 12.4% for GPT-4.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $30 / $60 for GPT-4.
- DeepSeek-V3.2-Speciale accepts more context: 128K tokens versus 8K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | GPT-4 | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.7 | 29.1 |
| Released | 2025-12-01 | 2023-03-14 |
| Weights | Open | Proprietary |
| Context window | 128K | 8K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.58 | $30 |
| Output $ / M tokens | $1.68 | $60 |
| Results tracked | 3 | 38 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), GPT-4: 31.6 (#283)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| WeirdML | 46.7% | 12.4% |
| BigCodeBench Instruct | — | 46% |
| LMArena Coding | — | 1254 |
| BigCodeBench Complete | — | 57.2% |
| HumanEval+ | — | 79.3% |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: —
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| METR Time Horizons | — | 36.1% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), GPT-4: 17.8 (#289)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| SimpleBench | 52.6% | — |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | — | 1241 |
| Mystery Game Puzzles | — | 12% |
| DTBench | — | 62.7% |
| LMCA | — | 17.1% |
| BIG-Bench Hard | — | 75.1% |
| Epoch Capabilities Index | — | 125.89 |
| ForecastBench | — | 57.8 |
| HellaSwag | — | 95.3% |
| WinoGrande | — | 87.5% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: 10.8 (#309)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 1.1% |
| LMArena Math | — | 1269 |
| MATH Level 5 | — | 23% |
| GSM8K | — | 92% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: 18.4 (#282)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| GPQA Diamond | — | 35.7% |
| LMArena Expert | — | 1211 |
| MMLU | — | 86.4% |
| TriviaQA | — | 84.8% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: 40.6 (#215)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| LMArena Non-English | — | 1246 |
| LMArena Chinese | — | 1242 |
| LMArena French | — | 1283 |
| LMArena German | — | 1251 |
| LMArena Japanese | — | 1209 |
| LMArena Korean | — | 1184 |
| LMArena Russian | — | 1251 |
| LMArena Spanish | — | 1261 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: 65.3 (#222)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| LMArena Instruction Following | — | 1241 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4: 37.7 (#212)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| LMArena Longer Query | — | 1244 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.0 (#222), GPT-4: 34.9 (#268)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4 |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 752 |
| LMArena Text | — | 1263 |
| LMArena Creative Writing | — | 1244 |
| LMArena Multi-Turn | — | 1257 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than GPT-4?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.1 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or GPT-4?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; GPT-4 lists at $30 and $60.
Is DeepSeek-V3.2-Speciale or GPT-4 better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3.2-Speciale does, with 128K tokens against 8K.
How many benchmarks do DeepSeek-V3.2-Speciale and GPT-4 share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and GPT-4 has 38.