Model comparison
Claude Opus 4.8 vs Llama 2-7B
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 29.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. Claude Opus 4.8 scores higher in 8 categories and Llama 2-7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.8 leads 64.7 to 15.7.
- The biggest single-benchmark swing is Chess Puzzles: 34% for Claude Opus 4.8 and 0% for Llama 2-7B.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.8 | Llama 2-7B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 60.7 | 29.1 |
| Released | 2026-05-28 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $5 | — |
| Output $ / M tokens | $25 | — |
| Results tracked | 65 | 29 |
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Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 59.9 (#12), Llama 2-7B: 29.2 (#307)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Coding | 1490 | 1002 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.8: 47.6 (#11), Llama 2-7B: —
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| APEX-Agents | 48.9% | — |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Claude Opus 4.8 leads
Claude Opus 4.8: 64.7 (#16), Llama 2-7B: 15.7 (#312)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| Chess Puzzles | 34% | 0% |
| LMArena Hard Prompts | 1482 | 1009 |
| Epoch Capabilities Index | 158.21 | 99.06 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 20.9% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| Mystery Game Puzzles | 36% | — |
| DTBench | 94.9% | — |
| LMCA | 57.5% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| BIG-Bench Hard | — | 39.2% |
| ForecastBench | 59.9 | — |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |
Math Claude Opus 4.8 leads
Claude Opus 4.8: 78.4 (#13), Llama 2-7B: 30.7 (#233)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Math | 1487 | 1042 |
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 69% | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
| GSM8K | — | 16.7% |
Knowledge Claude Opus 4.8 leads
Claude Opus 4.8: 61.3 (#29), Llama 2-7B: 28.2 (#248)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Expert | 1502 | 1036 |
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), Llama 2-7B: —
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
| ScienceQA | — | 43.1% |
Multilingual Claude Opus 4.8 leads
Claude Opus 4.8: 55.2 (#33), Llama 2-7B: 23.8 (#293)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Non-English | 1450 | 973 |
| LMArena Chinese | 1507 | 973 |
| LMArena French | 1481 | 970 |
| LMArena German | 1472 | 978 |
| LMArena Russian | 1474 | 995 |
| LMArena Spanish | 1466 | 1007 |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
Instruction Following Claude Opus 4.8 leads
Claude Opus 4.8: 77.4 (#24), Llama 2-7B: 50.8 (#298)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | 1476 | 1006 |
Long Context Claude Opus 4.8 leads
Claude Opus 4.8: 45.4 (#35), Llama 2-7B: 30.4 (#287)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | 1483 | 999 |
Writing & Preference Claude Opus 4.8 leads
Claude Opus 4.8: 72.0 (#16), Llama 2-7B: 28.0 (#298)
| Benchmark | Claude Opus 4.8 | Llama 2-7B |
|---|---|---|
| LMArena Text | 1461 | 1053 |
| LMArena Creative Writing | 1454 | 1033 |
| LMArena Multi-Turn | 1476 | 1029 |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
Frequently asked questions
Is Claude Opus 4.8 better than Llama 2-7B?
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 29.1 on the Noometry Index.
Is Claude Opus 4.8 or Llama 2-7B better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 29.2 in the Noometry coding category.
How many benchmarks do Claude Opus 4.8 and Llama 2-7B share?
17 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Llama 2-7B has 29.