Model comparison
DeepSeek-V3.2-Speciale vs Llama 3.1-405B
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 30.7 on the Noometry Index.
Last verified . 3 shared benchmarks.
DeepSeek
MetaSummary
- They share 3 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Llama 3.1-405B 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 16.8.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 23% for Llama 3.1-405B.
Side by side
| DeepSeek-V3.2-Speciale | Llama 3.1-405B | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 39.7 | 30.7 |
| Released | 2025-12-01 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 42 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Llama 3.1-405B: 33.1 (#262)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| WeirdML | 46.7% | 21.4% |
| LMArena Coding | — | 1291 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 21.0 (#140)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Llama 3.1-405B: 16.8 (#300)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 52.6% | 23% |
| Kagi LLM Benchmark | — | 45% |
| LMArena Hard Prompts | — | 1269 |
| DTBench | — | 61.4% |
| BIG-Bench Hard | — | 82.9% |
| Epoch Capabilities Index | — | 128.75 |
| ForecastBench | — | 59.9 |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 18.4 (#290)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 9.7% |
| Omni-MATH | — | 24.9% |
| LMArena Math | — | 1281 |
| MATH Level 5 | — | 49.8% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 30.4 (#227)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | — | 50.9% |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| GPQA (HELM) | — | 52.2% |
| LMArena Expert | — | 1243 |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 40.7 (#214)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | — | 1248 |
| LMArena Chinese | — | 1242 |
| LMArena French | — | 1279 |
| LMArena German | — | 1252 |
| LMArena Japanese | — | 1208 |
| LMArena Korean | — | 1184 |
| LMArena Russian | — | 1265 |
| LMArena Spanish | — | 1260 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 65.9 (#214)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| IFEval | — | 81.1% |
| LMArena Instruction Following | — | 1259 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Llama 3.1-405B: 38.4 (#197)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | — | 1266 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Llama 3.1-405B: 38.9 (#251)
| Benchmark | DeepSeek-V3.2-Speciale | Llama 3.1-405B |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 870 |
| LMArena Text | — | 1284 |
| LMArena Creative Writing | — | 1262 |
| WildBench | — | 78.3% |
| LMArena Multi-Turn | — | 1297 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Llama 3.1-405B?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 30.7 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Llama 3.1-405B better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 33.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Llama 3.1-405B share?
3 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Llama 3.1-405B has 42.