Model comparison
DeepSeek-V3.2-Speciale vs Gemini 1.5 Pro (May 2024)
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 32.1 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeek
GoogleSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 2 categories and Gemini 1.5 Pro (May 2024) in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 12.3.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 27.1% for Gemini 1.5 Pro (May 2024).
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.7 | 32.1 |
| Released | 2025-12-01 | 2024-02-15 |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 45 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Gemini 1.5 Pro (May 2024): 34.2 (#241)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| WeirdML | 46.7% | 22.2% |
| BigCodeBench Instruct | — | 43.8% |
| LMArena Coding | — | 1294 |
| BigCodeBench Complete | — | 57.5% |
| CadEval | — | 34% |
| HumanEval+ | — | 79.3% |
| MBPP+ | — | 74.6% |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 17.9 (#145)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| TheAgentCompany | — | 3.4% |
| Cybench | — | 7.5% |
| BALROG | — | 21% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Gemini 1.5 Pro (May 2024): 12.3 (#338)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| SimpleBench | 52.6% | 27.1% |
| ARC-AGI-2 | — | 0.8% |
| LMArena Hard Prompts | — | 1296 |
| DTBench | — | 59% |
| BIG-Bench Hard | — | 89.2% |
| Epoch Capabilities Index | — | 131.73 |
| ForecastBench | — | 58.4 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 25.8 (#266)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 23.1% |
| Omni-MATH | — | 36.4% |
| LMArena Math | — | 1315 |
| MATH Level 5 | — | 70.4% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 29.4 (#239)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| GPQA Diamond | — | 57.2% |
| Humanity's Last Exam | — | 4.6% |
| MMLU-Pro | — | 73.7% |
| Confabulations | — | 13.5% |
| GPQA (HELM) | — | 53.4% |
| LMArena Expert | — | 1279 |
| MMLU | — | 86.9% |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 36.8 (#77)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Vision | — | 1161 |
| Video-MME | — | 75% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 45.3 (#174)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Non-English | — | 1312 |
| LMArena Chinese | — | 1331 |
| LMArena French | — | 1302 |
| LMArena German | — | 1286 |
| LMArena Japanese | — | 1292 |
| LMArena Korean | — | 1298 |
| LMArena Russian | — | 1320 |
| LMArena Spanish | — | 1311 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 68.6 (#185)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| IFEval | — | 83.7% |
| LMArena Instruction Following | — | 1297 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Pro (May 2024): 39.8 (#169)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Longer Query | — | 1308 |
Writing & Preference Gemini 1.5 Pro (May 2024) leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Gemini 1.5 Pro (May 2024): 52.4 (#172)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Text | — | 1319 |
| LMArena Creative Writing | — | 1333 |
| EQ-Bench Creative Writing | 1276 | — |
| WildBench | — | 81.3% |
| LMArena Multi-Turn | — | 1296 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Gemini 1.5 Pro (May 2024)?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 32.1 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Gemini 1.5 Pro (May 2024) better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 34.2 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 1.5 Pro (May 2024) share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 1.5 Pro (May 2024) has 45.