# Claude Opus 5 vs Llama 4 Scout

> Claude Opus 5 is the stronger model overall, scoring 67.7 to 27.4 on the Noometry Index. Llama 4 Scout costs 67× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-5-vs-llama-4-scout
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Claude Opus 5 scores higher in 10 categories and Llama 4 Scout in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5 leads 77.1 to 9.2.
- The biggest single-benchmark swing is ARC-AGI-1: 97.5% for Claude Opus 5 and 0.5% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $5 / $25 for Claude Opus 5.
- Claude Opus 5 accepts more context: 1M tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 67.7 | 27.4 |
| Rank | 4 | 323 |
| Context | 1M | 128K |
| Input $/M | $5 | $0.10 |
| Output $/M | $25 | $0.30 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 5: 67.0 (#5)
- Llama 4 Scout: 19.9 (#334)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| SciCode | 56.4% | 17% |
| LMArena Coding | 1533 | 1286 |
| DeepSWE | 73.6% | — |
| FrontierCode | 53.4% | — |
| SWE-bench Verified (bash only) | — | 9.1% |
| CursorBench | 46.6% | — |
| LMArena WebDev | 1694 | — |
| FrontierSWE | 52% | — |
| WeirdML | 91.8% | — |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 2,165 | — |

## Agentic & Tool Use

- Claude Opus 5: 55.5 (#1)
- Llama 4 Scout: 24.4 (#109)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| APEX-Agents | 65.8% | — |
| Berkeley Function Calling Leaderboard | — | 28.1% |
| OSWorld 2.0 | 31.4% | — |
| τ²-bench Banking | 48.7% | — |
| PostTrainBench | 35% | — |
| BALROG | 63.4% | — |
| GBAEval | 79.6% | — |
| GDP.pdf | 24% | — |
| Vending-Bench 2 | 11,182 | — |

## Reasoning

- Claude Opus 5: 77.1 (#3)
- Llama 4 Scout: 9.2 (#339)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| ARC-AGI-2 | 90.4% | 0% |
| ARC-AGI-1 | 97.5% | 0.5% |
| CritPt | 29.1% | 0% |
| LMArena Hard Prompts | 1525 | 1266 |
| DTBench | 97.9% | 57.9% |
| LMCA | 64.5% | 12% |
| Epoch Capabilities Index | 162.67 | 129.64 |
| SimpleBench | 80.6% | — |
| Kagi LLM Benchmark | — | 36.9% |
| NYT Connections (extended) | 94.3% | — |
| Chess Puzzles | 42% | — |
| EBR-Bench | 45.7% | — |
| Mystery Game Puzzles | 59% | — |
| Bench to the Future 3 | 0.12 | — |
| ForecastBench | — | 57.5 |

## Math

- Claude Opus 5: 86.1 (#6)
- Llama 4 Scout: 18.4 (#280)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.9% | 7.8% |
| LMArena Math | 1533 | 1286 |
| FrontierMath (Tiers 1-3) | 85.6% | — |
| FrontierMath Tier 4 | 73.2% | — |
| ProofBench | 99% | — |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |

## Knowledge

- Claude Opus 5: 66.8 (#8)
- Llama 4 Scout: 31.8 (#208)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 93.9% | 51.8% |
| LMArena Expert | 1558 | 1236 |
| SimpleQA Verified | 59.9% | — |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |

## Multimodal

- Claude Opus 5: 51.1 (#6)
- Llama 4 Scout: 31.6 (#98)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1321 | 1118 |
| Blueprint-Bench 2 | 30.4% | — |
| Furniture Assembly | 60.8% | — |
| LMArena Document | 1516 | — |
| SpatialViz-Bench | — | 34.2% |

## Multilingual

- Claude Opus 5: 58.8 (#3)
- Llama 4 Scout: 41.3 (#207)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1500 | 1253 |
| LMArena Chinese | 1575 | 1256 |
| LMArena French | 1522 | 1283 |
| LMArena German | 1522 | 1274 |
| LMArena Japanese | 1510 | 1209 |
| LMArena Korean | 1526 | 1207 |
| LMArena Russian | 1507 | 1263 |
| LMArena Spanish | 1519 | 1277 |

## Instruction Following

- Claude Opus 5: 79.3 (#5)
- Llama 4 Scout: 66.0 (#212)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1516 | 1248 |
| IFEval | — | 81.8% |

## Long Context

- Claude Opus 5: 46.5 (#20)
- Llama 4 Scout: 27.5 (#289)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1516 | 1265 |
| Fiction.LiveBench | — | 36% |

## Writing & Preference

- Claude Opus 5: 79.3 (#2)
- Llama 4 Scout: 37.1 (#256)

| Benchmark | Claude Opus 5 | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1506 | 1279 |
| LMArena Creative Writing | 1491 | 1249 |
| EQ-Bench Creative Writing | 2133 | 783 |
| LMArena Multi-Turn | 1496 | 1281 |
| WildBench | — | 78% |
| EQ-Bench 4 | 1385 | — |

## FAQ

### Is Claude Opus 5 better than Llama 4 Scout?

Claude Opus 5 is the stronger model overall, scoring 67.7 to 27.4 on the Noometry Index. Llama 4 Scout costs 67× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 5 or Llama 4 Scout?

Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Claude Opus 5 lists at $5 and $25.

### Is Claude Opus 5 or Llama 4 Scout better for coding?

Claude Opus 5 scores higher on coding benchmarks: 67.0 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 5 does, with 1M tokens against 128K.

### How many benchmarks do Claude Opus 5 and Llama 4 Scout share?

28 benchmarks have published results for both models. Claude Opus 5 has 57 scored results on Noometry and Llama 4 Scout has 43.