Model comparison
Claude Sonnet 4.6 vs Llama 2-7B
Claude Sonnet 4.6 is the stronger model overall, scoring 50.1 to 28.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 8 categories and Llama 2-7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Sonnet 4.6 leads 70.4 to 28.1.
- The biggest single-benchmark swing is Chess Puzzles: 13% for Claude Sonnet 4.6 and 0% for Llama 2-7B.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.6 | Llama 2-7B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 50.1 | 28.6 |
| Released | 2026-02-17 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $3 | — |
| Output $ / M tokens | $15 | — |
| Results tracked | 57 | 29 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.0 (#62), Llama 2-7B: 28.7 (#302)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Coding | 1504 | 1002 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| LMArena WebDev | 1521 | — |
| SciCode | 46.8% | — |
| WeirdML | 66.1% | — |
| ALE-Bench | 1,327 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#26), Llama 2-7B: —
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#40), Llama 2-7B: 15.1 (#309)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| Chess Puzzles | 13% | 0% |
| LMArena Hard Prompts | 1485 | 1009 |
| Epoch Capabilities Index | 152.25 | 98.54 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Thematic Generalization | 76.3% | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| BIG-Bench Hard | — | 39.2% |
| ForecastBench | 62 | — |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.9 (#41), Llama 2-7B: 28.2 (#231)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Math | 1463 | 1042 |
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
| GSM8K | — | 16.7% |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.6 (#60), Llama 2-7B: 27.7 (#243)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Expert | 1500 | 1036 |
| GPQA Diamond | 87.4% | — |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#61), Llama 2-7B: —
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
| ScienceQA | — | 43.1% |
Multilingual Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 54.6 (#39), Llama 2-7B: 23.9 (#288)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Non-English | 1440 | 973 |
| LMArena Chinese | 1491 | 973 |
| LMArena French | 1465 | 969 |
| LMArena German | 1428 | 978 |
| LMArena Russian | 1440 | 995 |
| LMArena Spanish | 1465 | 1007 |
| LMArena Japanese | 1419 | — |
| LMArena Korean | 1411 | — |
Instruction Following Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 77.6 (#23), Llama 2-7B: 51.0 (#293)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | 1476 | 1006 |
Long Context Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 45.3 (#40), Llama 2-7B: 30.4 (#282)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | 1479 | 999 |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.4 (#22), Llama 2-7B: 28.1 (#293)
| Benchmark | Claude Sonnet 4.6 | Llama 2-7B |
|---|---|---|
| LMArena Text | 1458 | 1053 |
| LMArena Creative Writing | 1435 | 1033 |
| LMArena Multi-Turn | 1464 | 1029 |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than Llama 2-7B?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.1 to 28.6 on the Noometry Index.
Is Claude Sonnet 4.6 or Llama 2-7B better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.0 versus 28.7 in the Noometry coding category.
How many benchmarks do Claude Sonnet 4.6 and Llama 2-7B share?
17 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and Llama 2-7B has 29.