Model comparison
DeepSeek-V2.5 (Sep 2024) vs Llama 3.2 90B
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 27.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
MetaSummary
- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 35.9 to 11.1.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 37.6 | 27.5 |
| Released | 2024-09-06 | 2024-09-24 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 9 |
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Category by category
Coding Not comparable
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Llama 3.2 90B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1309 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2.5 (Sep 2024): —, Llama 3.2 90B: 30.0 (#80)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| BALROG | — | 27.3% |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Llama 3.2 90B: 21.7 (#217)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| EnigmaEval | — | 0.4% |
| LMArena Hard Prompts | 1289 | — |
| Epoch Capabilities Index | — | 125.5 |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Llama 3.2 90B: 11.1 (#308)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.6% |
| LMArena Math | 1288 | — |
| MATH Level 5 | — | 39.4% |
Knowledge DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Llama 3.2 90B: 21.7 (#274)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| GPQA Diamond | — | 41% |
| LMArena Expert | 1266 | — |
| MMLU | — | 80.3% |
Multimodal Not comparable
DeepSeek-V2.5 (Sep 2024): —, Llama 3.2 90B: 25.4 (#124)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| LMArena Vision | — | 1000 |
| GeoBench | — | 52% |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Llama 3.2 90B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena Chinese | 1318 | — |
| LMArena French | 1289 | — |
| LMArena German | 1258 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Russian | 1289 | — |
| LMArena Spanish | 1248 | — |
Instruction Following Not comparable
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Llama 3.2 90B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Llama 3.2 90B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Not comparable
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Llama 3.2 90B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 3.2 90B |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Llama 3.2 90B?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 27.5 on the Noometry Index.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Llama 3.2 90B share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Llama 3.2 90B has 9.