Model comparison
Claude 3.7 Sonnet vs Llama 3.1-405B
Claude 3.7 Sonnet is the stronger model overall, scoring 39.5 to 30.7 on the Noometry Index.
Last verified . 32 shared benchmarks.
MetaSummary
- They share 32 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 9 categories and Llama 3.1-405B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude 3.7 Sonnet leads 37.5 to 18.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 57.8% for Claude 3.7 Sonnet and 9.7% for Llama 3.1-405B.
- Llama 3.1-405B has downloadable open weights; the other is API-only.
Side by side
| Claude 3.7 Sonnet | Llama 3.1-405B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 39.5 | 30.7 |
| Released | 2025-02-24 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 58 | 42 |
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Category by category
Coding Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 40.6 (#136), Llama 3.1-405B: 33.1 (#262)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| LMArena Coding | 1361 | 1291 |
| SWE-bench Verified | 61% | — |
| SWE-bench Verified (bash only) | 52.8% | — |
| Aider Polyglot | 64.9% | — |
| GSO | 3.8% | — |
| WeirdML | — | 21.4% |
| LiveBench Coding | 74.5% | — |
| CadEval | 54% | — |
Agentic & Tool Use Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 34.1 (#50), Llama 3.1-405B: 21.0 (#140)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| TheAgentCompany | 30.9% | 7.4% |
| Cybench | 20% | 7.5% |
| DeepResearch Bench | 43.6% | — |
| OSWorld | 35.8% | — |
| METR Time Horizons | 60% | — |
Reasoning Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 18.6 (#277), Llama 3.1-405B: 16.8 (#300)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 46.4% | 23% |
| LMArena Hard Prompts | 1333 | 1269 |
| Epoch Capabilities Index | 141.16 | 128.75 |
| ForecastBench | 61.8 | 59.9 |
| ARC-AGI-2 | 0.9% | — |
| Kagi LLM Benchmark | — | 45% |
| ARC-AGI-1 | 28.6% | — |
| EnigmaEval | 4.2% | — |
| LiveBench Reasoning | 87.8% | — |
| DTBench | — | 61.4% |
| LiveBench Data Analysis | 74% | — |
| BIG-Bench Hard | — | 82.9% |
| HellaSwag | — | 89.2% |
| LiveBench | 76.1% | — |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |
Math Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 37.5 (#153), Llama 3.1-405B: 18.4 (#290)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 57.8% | 9.7% |
| Omni-MATH | 33% | 24.9% |
| LMArena Math | 1337 | 1281 |
| MATH Level 5 | 91.2% | 49.8% |
| LiveBench Math | 79% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
Knowledge Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 39.8 (#130), Llama 3.1-405B: 30.4 (#227)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | 79.7% | 50.9% |
| MMLU-Pro | 78.4% | 72.3% |
| Confabulations | 14.7% | 17.6% |
| GPQA (HELM) | 60.8% | 52.2% |
| LMArena Expert | 1321 | 1243 |
| Humanity's Last Exam | 8% | — |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |
Multimodal Not comparable
Claude 3.7 Sonnet: 33.7 (#95), Llama 3.1-405B: —
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| LMArena Vision | 1169 | — |
| GeoBench | 68% | — |
| VPCT | 39% | — |
| SpatialViz-Bench | 33.9% | — |
Multilingual Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 44.1 (#179), Llama 3.1-405B: 40.7 (#214)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1296 | 1248 |
| LMArena Chinese | 1299 | 1242 |
| LMArena French | 1303 | 1279 |
| LMArena German | 1301 | 1252 |
| LMArena Japanese | 1267 | 1208 |
| LMArena Korean | 1249 | 1184 |
| LMArena Russian | 1311 | 1265 |
| LMArena Spanish | 1298 | 1260 |
Instruction Following Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 72.9 (#125), Llama 3.1-405B: 65.9 (#214)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| IFEval | 83.4% | 81.1% |
| LMArena Instruction Following | 1352 | 1259 |
| LiveBench Instruction Following | 81.3% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.3 (#10), Llama 3.1-405B: 38.4 (#197)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1373 | 1266 |
| Fiction.LiveBench | 83.3% | — |
Writing & Preference Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 54.4 (#150), Llama 3.1-405B: 38.9 (#251)
| Benchmark | Claude 3.7 Sonnet | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1314 | 1284 |
| LMArena Creative Writing | 1332 | 1262 |
| EQ-Bench Creative Writing | 1412 | 870 |
| WildBench | 81.4% | 78.3% |
| LMArena Multi-Turn | 1339 | 1297 |
| Short-Story Creative Writing | 81.1% | — |
| LiveBench Language | 59.9% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than Llama 3.1-405B?
Claude 3.7 Sonnet is the stronger model overall, scoring 39.5 to 30.7 on the Noometry Index.
Is Claude 3.7 Sonnet or Llama 3.1-405B better for coding?
Claude 3.7 Sonnet scores higher on coding benchmarks: 40.6 versus 33.1 in the Noometry coding category.
How many benchmarks do Claude 3.7 Sonnet and Llama 3.1-405B share?
32 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and Llama 3.1-405B has 42.