Model comparison
DeepSeek-V3.2-Speciale vs Llama2 70b Steerlm Chat
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
NVIDIASummary
- The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.0 to 31.6.
Side by side
| DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat | |
|---|---|---|
| Provider | DeepSeek | NVIDIA |
| Noometry Index | 39.7 | 31.8 |
| Released | 2025-12-01 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 9 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Llama2 70b Steerlm Chat: 29.9 (#300)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1025 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Llama2 70b Steerlm Chat: 20.0 (#246)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1047 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Llama2 70b Steerlm Chat: 31.3 (#226)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | — | 1072 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Llama2 70b Steerlm Chat: 28.8 (#270)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | — | 1063 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Llama2 70b Steerlm Chat: 54.2 (#279)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | — | 1060 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Llama2 70b Steerlm Chat: 30.4 (#288)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | — | 998 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Llama2 70b Steerlm Chat: 31.6 (#283)
| Benchmark | DeepSeek-V3.2-Speciale | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | — | 1098 |
| LMArena Creative Writing | — | 1091 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1058 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Llama2 70b Steerlm Chat?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.8 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Llama2 70b Steerlm Chat better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 29.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Llama2 70b Steerlm Chat share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Llama2 70b Steerlm Chat has 9.