Model comparison
Claude Opus 4.7 vs Llama 3.1-405B
Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 30.4 on the Noometry Index.
Last verified . 26 shared benchmarks.
MetaSummary
- They share 26 benchmarks with published results for both. Claude Opus 4.7 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 Opus 4.7 leads 66.5 to 17.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 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 Opus 4.7 | Llama 3.1-405B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 58.4 | 30.4 |
| Released | 2026-04-14 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $5 | — |
| Output $ / M tokens | $25 | — |
| Results tracked | 66 | 42 |
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Category by category
Coding Claude Opus 4.7 leads
Claude Opus 4.7: 59.9 (#10), Llama 3.1-405B: 32.7 (#257)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| WeirdML | 76.4% | 21.4% |
| LMArena Coding | 1519 | 1291 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| LMArena WebDev | 1557 | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |
Agentic & Tool Use Claude Opus 4.7 leads
Claude Opus 4.7: 47.9 (#8), Llama 3.1-405B: 20.9 (#131)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| TheAgentCompany | — | 7.4% |
| τ²-bench Banking | 40.2% | — |
| Cybench | — | 7.5% |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Claude Opus 4.7 leads
Claude Opus 4.7: 53.7 (#24), Llama 3.1-405B: 16.4 (#293)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 61.7% | 23% |
| Kagi LLM Benchmark | 80.7% | 45% |
| LMArena Hard Prompts | 1507 | 1270 |
| DTBench | 94.7% | 61.4% |
| Epoch Capabilities Index | 156.39 | 128.76 |
| ForecastBench | 60.3 | 59.9 |
| ARC-AGI-2 | 75.8% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| CritPt | 12% | — |
| Chess Puzzles | 30% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| LMCA | 52.2% | — |
| BIG-Bench Hard | — | 82.9% |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |
Math Claude Opus 4.7 leads
Claude Opus 4.7: 66.5 (#20), Llama 3.1-405B: 17.3 (#283)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 9.7% |
| LMArena Math | 1499 | 1281 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Claude Opus 4.7 leads
Claude Opus 4.7: 62.6 (#20), Llama 3.1-405B: 30.4 (#221)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | 90.2% | 50.9% |
| LMArena Expert | 1521 | 1243 |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |
Multimodal Not comparable
Claude Opus 4.7: 41.5 (#29), Llama 3.1-405B: —
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| LMArena Vision | 1317 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |
Multilingual Claude Opus 4.7 leads
Claude Opus 4.7: 57.5 (#9), Llama 3.1-405B: 40.9 (#209)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1481 | 1248 |
| LMArena Chinese | 1530 | 1242 |
| LMArena French | 1505 | 1278 |
| LMArena German | 1494 | 1252 |
| LMArena Japanese | 1472 | 1208 |
| LMArena Korean | 1466 | 1184 |
| LMArena Russian | 1494 | 1265 |
| LMArena Spanish | 1497 | 1259 |
Instruction Following Claude Opus 4.7 leads
Claude Opus 4.7: 78.6 (#9), Llama 3.1-405B: 66.1 (#209)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1498 | 1259 |
| IFEval | — | 81.1% |
Long Context Claude Opus 4.7 leads
Claude Opus 4.7: 46.1 (#24), Llama 3.1-405B: 38.4 (#192)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1505 | 1266 |
Writing & Preference Claude Opus 4.7 leads
Claude Opus 4.7: 75.3 (#8), Llama 3.1-405B: 39.1 (#246)
| Benchmark | Claude Opus 4.7 | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1491 | 1284 |
| LMArena Creative Writing | 1486 | 1262 |
| EQ-Bench Creative Writing | 1914 | 870 |
| LMArena Multi-Turn | 1506 | 1297 |
| WildBench | — | 78.3% |
| EQ-Bench 4 | 1311 | — |
Frequently asked questions
Is Claude Opus 4.7 better than Llama 3.1-405B?
Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 30.4 on the Noometry Index.
Is Claude Opus 4.7 or Llama 3.1-405B better for coding?
Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 32.7 in the Noometry coding category.
How many benchmarks do Claude Opus 4.7 and Llama 3.1-405B share?
26 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Llama 3.1-405B has 42.