Model comparison
Claude Opus 4.6 vs Llama 13b
Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 24.4 on the Noometry Index.
Last verified . 9 shared benchmarks.
MetaSummary
- They share 9 benchmarks with published results for both. Claude Opus 4.6 scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Opus 4.6 leads 73.5 to 13.8.
- Llama 13b has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.6 | Llama 13b | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 58.2 | 24.4 |
| Released | 2026-02-04 | 2023-02-24 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $5 | — |
| Output $ / M tokens | $25 | — |
| Results tracked | 68 | 21 |
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Category by category
Coding Claude Opus 4.6 leads
Claude Opus 4.6: 57.2 (#20), Llama 13b: 21.4 (#337)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Coding | 1536 | 683 |
| SWE-bench Verified | 78.7% | — |
| FrontierCode | 26.6% | — |
| SWE-bench Verified (bash only) | 75.6% | — |
| LMArena WebDev | 1547 | — |
| SWE-bench Multilingual | 72% | — |
| GSO | 41.2% | — |
| WeirdML | 78% | — |
| ALE-Bench | 996.5 | — |
| AlgoTune | 1.47 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.6: 51.1 (#4), Llama 13b: —
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| Terminal-Bench | 79.8% | — |
| APEX-Agents | 46.3% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |
Reasoning Claude Opus 4.6 leads
Claude Opus 4.6: 57.8 (#23), Llama 13b: 14.0 (#329)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Hard Prompts | 1527 | 728 |
| Epoch Capabilities Index | 155.24 | 100.58 |
| ARC-AGI-2 | 69.2% | — |
| SimpleBench | 67.6% | — |
| Kagi LLM Benchmark | 83.6% | — |
| NYT Connections (extended) | 92.1% | — |
| ARC-AGI-1 | 94% | — |
| Chess Puzzles | 17% | — |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| Mystery Game Puzzles | 25% | — |
| DTBench | 91.2% | — |
| LMCA | 55.8% | — |
| BIG-Bench Hard | — | 37.9% |
| ForecastBench | 60 | — |
| HellaSwag | — | 79.2% |
| LAMBADA | — | 75.2% |
| PIQA | — | 80.1% |
| WinoGrande | — | 73% |
Math Claude Opus 4.6 leads
Claude Opus 4.6: 63.0 (#31), Llama 13b: 26.7 (#256)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Math | 1519 | 838 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 78.5% | — |
| OTIS Mock AIME 2024-2025 | 94.4% | — |
| ProofBench | 50% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
| GSM8K | — | 20.6% |
Knowledge Not comparable
Claude Opus 4.6: 61.9 (#26), Llama 13b: —
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| GPQA Diamond | 90.5% | — |
| Humanity's Last Exam | 34.4% | — |
| SimpleQA Verified | 47% | — |
| Vectara Hallucination Rate | 12.2% | — |
| LMArena Expert | 1546 | — |
| ARC (AI2) Challenge | — | 52.7% |
| BoolQ | — | 78.7% |
| MMLU | — | 47.7% |
| OpenBookQA | — | 56.4% |
| TriviaQA | — | 77.9% |
Multimodal Not comparable
Claude Opus 4.6: 37.3 (#74), Llama 13b: —
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 28.3% | — |
| LMArena Document | 1507 | — |
| ScienceQA | — | 43.3% |
Multilingual Claude Opus 4.6 leads
Claude Opus 4.6: 57.9 (#6), Llama 13b: 16.6 (#297)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Non-English | 1489 | 819 |
| LMArena Chinese | 1551 | — |
| LMArena French | 1513 | — |
| LMArena German | 1502 | — |
| LMArena Japanese | 1484 | — |
| LMArena Korean | 1464 | — |
| LMArena Russian | 1497 | — |
| LMArena Spanish | 1510 | — |
Instruction Following Claude Opus 4.6 leads
Claude Opus 4.6: 79.5 (#4), Llama 13b: 36.7 (#305)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Instruction Following | 1523 | 781 |
Long Context Not comparable
Claude Opus 4.6: 48.1 (#13), Llama 13b: —
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |
| LMArena Longer Query | 1520 | — |
Writing & Preference Claude Opus 4.6 leads
Claude Opus 4.6: 73.5 (#10), Llama 13b: 13.8 (#312)
| Benchmark | Claude Opus 4.6 | Llama 13b |
|---|---|---|
| LMArena Text | 1503 | 834 |
| LMArena Creative Writing | 1505 | 794 |
| LMArena Multi-Turn | 1513 | 753 |
| EQ-Bench Creative Writing | 1809 | — |
| EQ-Bench 4 | 1223 | — |
Frequently asked questions
Is Claude Opus 4.6 better than Llama 13b?
Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 24.4 on the Noometry Index.
Is Claude Opus 4.6 or Llama 13b better for coding?
Claude Opus 4.6 scores higher on coding benchmarks: 57.2 versus 21.4 in the Noometry coding category.
How many benchmarks do Claude Opus 4.6 and Llama 13b share?
9 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and Llama 13b has 21.