Model comparison
Claude Sonnet 5 vs Llama 3.1-405B
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 30.4 on the Noometry Index.
Last verified . 25 shared benchmarks.
MetaSummary
- They share 25 benchmarks with published results for both. Claude Sonnet 5 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 Sonnet 5 leads 66.1 to 17.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.7% for Claude Sonnet 5 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 Sonnet 5 | Llama 3.1-405B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 54.5 | 30.4 |
| Released | 2026-06-29 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 51 | 42 |
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Category by category
Coding Claude Sonnet 5 leads
Claude Sonnet 5: 55.5 (#20), Llama 3.1-405B: 32.7 (#257)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| WeirdML | 68.8% | 21.4% |
| LMArena Coding | 1483 | 1291 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| LMArena WebDev | 1540 | — |
| SciCode | 53.6% | — |
| GSO | 37.3% | — |
| ALE-Bench | 1,463 | — |
Agentic & Tool Use Claude Sonnet 5 leads
Claude Sonnet 5: 42.7 (#16), Llama 3.1-405B: 20.9 (#131)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| APEX-Agents | 54.5% | — |
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |
Reasoning Claude Sonnet 5 leads
Claude Sonnet 5: 48.2 (#37), Llama 3.1-405B: 16.4 (#293)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 60.6% | 23% |
| LMArena Hard Prompts | 1461 | 1270 |
| DTBench | 92.5% | 61.4% |
| Epoch Capabilities Index | 156.34 | 128.76 |
| ForecastBench | 61.1 | 59.9 |
| Kagi LLM Benchmark | — | 45% |
| NYT Connections (extended) | 75.1% | — |
| CritPt | 16.9% | — |
| Chess Puzzles | 35% | — |
| Mystery Game Puzzles | 35% | — |
| LMCA | 50% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| BIG-Bench Hard | — | 82.9% |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |
Math Claude Sonnet 5 leads
Claude Sonnet 5: 66.1 (#21), Llama 3.1-405B: 17.3 (#283)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.7% | 9.7% |
| LMArena Math | 1467 | 1281 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 77% | — |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |
Knowledge Claude Sonnet 5 leads
Claude Sonnet 5: 55.7 (#42), Llama 3.1-405B: 30.4 (#221)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | 90.5% | 50.9% |
| LMArena Expert | 1491 | 1243 |
| SimpleQA Verified | 33.7% | — |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |
Multimodal Not comparable
Claude Sonnet 5: 42.4 (#26), Llama 3.1-405B: —
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| LMArena Vision | 1275 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |
Multilingual Claude Sonnet 5 leads
Claude Sonnet 5: 54.0 (#55), Llama 3.1-405B: 40.9 (#209)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1431 | 1248 |
| LMArena Chinese | 1475 | 1242 |
| LMArena French | 1457 | 1278 |
| LMArena German | 1448 | 1252 |
| LMArena Japanese | 1422 | 1208 |
| LMArena Korean | 1411 | 1184 |
| LMArena Russian | 1452 | 1265 |
| LMArena Spanish | 1436 | 1259 |
Instruction Following Claude Sonnet 5 leads
Claude Sonnet 5: 76.6 (#39), Llama 3.1-405B: 66.1 (#209)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1453 | 1259 |
| IFEval | — | 81.1% |
Long Context Claude Sonnet 5 leads
Claude Sonnet 5: 44.8 (#53), Llama 3.1-405B: 38.4 (#192)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1464 | 1266 |
Writing & Preference Claude Sonnet 5 leads
Claude Sonnet 5: 69.4 (#24), Llama 3.1-405B: 39.1 (#246)
| Benchmark | Claude Sonnet 5 | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1443 | 1284 |
| LMArena Creative Writing | 1416 | 1262 |
| EQ-Bench Creative Writing | 1794 | 870 |
| LMArena Multi-Turn | 1454 | 1297 |
| WildBench | — | 78.3% |
| EQ-Bench 4 | 1236 | — |
Frequently asked questions
Is Claude Sonnet 5 better than Llama 3.1-405B?
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 30.4 on the Noometry Index.
Is Claude Sonnet 5 or Llama 3.1-405B better for coding?
Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 32.7 in the Noometry coding category.
How many benchmarks do Claude Sonnet 5 and Llama 3.1-405B share?
25 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and Llama 3.1-405B has 42.