Model comparison
Deepseek Coder v2 vs Llama 3.2 90B
Deepseek Coder v2 is the stronger model overall, scoring 35.3 to 27.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
MetaSummary
- The widest gap is in math, where Deepseek Coder v2 leads 32.3 to 10.4.
Side by side
| Deepseek Coder v2 | Llama 3.2 90B | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 35.3 | 27.1 |
| Released | 2024-06-17 | 2024-09-24 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 24 | 9 |
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Category by category
Coding Not comparable
Deepseek Coder v2: 37.5 (#178), Llama 3.2 90B: —
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| BigCodeBench Instruct | 48.2% | — |
| LMArena Coding | 1251 | — |
| BigCodeBench Complete | 59.7% | — |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |
Agentic & Tool Use Not comparable
Deepseek Coder v2: —, Llama 3.2 90B: 29.7 (#73)
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| BALROG | — | 27.3% |
Reasoning Deepseek Coder v2 leads
Deepseek Coder v2: 22.6 (#175), Llama 3.2 90B: 20.9 (#207)
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| EnigmaEval | — | 0.4% |
| LMArena Hard Prompts | 1207 | — |
| Epoch Capabilities Index | — | 125.5 |
| WinoGrande | 83.7% | — |
Math Deepseek Coder v2 leads
Deepseek Coder v2: 32.3 (#188), Llama 3.2 90B: 10.4 (#302)
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.6% |
| LMArena Math | 1241 | — |
| MATH Level 5 | — | 39.4% |
| GSM8K | 94.5% | — |
Knowledge Deepseek Coder v2 leads
Deepseek Coder v2: 31.7 (#209), Llama 3.2 90B: 21.7 (#269)
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| GPQA Diamond | — | 41% |
| LMArena Expert | 1181 | — |
| ARC (AI2) Challenge | 64.3% | — |
| MMLU | — | 80.3% |
Multimodal Not comparable
Deepseek Coder v2: —, Llama 3.2 90B: 24.9 (#119)
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| LMArena Vision | — | 1000 |
| GeoBench | — | 52% |
Multilingual Not comparable
Deepseek Coder v2: 36.4 (#235), Llama 3.2 90B: —
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| LMArena Non-English | 1182 | — |
| LMArena Chinese | 1201 | — |
| LMArena French | 1184 | — |
| LMArena German | 1164 | — |
| LMArena Japanese | 1126 | — |
| LMArena Korean | 1104 | — |
| LMArena Russian | 1188 | — |
| LMArena Spanish | 1153 | — |
Instruction Following Not comparable
Deepseek Coder v2: 61.9 (#237), Llama 3.2 90B: —
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| LMArena Instruction Following | 1180 | — |
Long Context Not comparable
Deepseek Coder v2: 37.0 (#219), Llama 3.2 90B: —
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| LMArena Longer Query | 1219 | — |
Writing & Preference Not comparable
Deepseek Coder v2: 38.4 (#249), Llama 3.2 90B: —
| Benchmark | Deepseek Coder v2 | Llama 3.2 90B |
|---|---|---|
| LMArena Text | 1191 | — |
| LMArena Creative Writing | 1120 | — |
| LMArena Multi-Turn | 1176 | — |
Frequently asked questions
Is Deepseek Coder v2 better than Llama 3.2 90B?
Deepseek Coder v2 is the stronger model overall, scoring 35.3 to 27.1 on the Noometry Index.
How many benchmarks do Deepseek Coder v2 and Llama 3.2 90B share?
0 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Llama 3.2 90B has 9.