# GPT-4o vs Llama 4 Scout

> GPT-4o is the stronger model overall, scoring 28.5 to 27.4 on the Noometry Index. Llama 4 Scout costs 29× less per token, which makes it the better buy when GPT-4o's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-4o-vs-llama-4-scout
- Last updated: 2026-10-10
- Shared benchmarks: 38

## Summary

- They share 38 benchmarks with published results for both. GPT-4o scores higher in 7 categories and Llama 4 Scout in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-4o leads 52.8 to 37.1.
- The biggest single-benchmark swing is Fiction.LiveBench: 66.7% for GPT-4o and 36% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $2.50 / $10 for GPT-4o.
- Llama 4 Scout has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4o | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 28.5 | 27.4 |
| Rank | 316 | 323 |
| Context | 128K | 128K |
| Input $/M | $2.50 | $0.10 |
| Output $/M | $10 | $0.30 |
| Weights | Proprietary | Open |

## Coding

- GPT-4o: 25.1 (#323)
- Llama 4 Scout: 19.9 (#334)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| SWE-bench Verified (bash only) | 21.6% | 9.1% |
| LMArena Coding | 1297 | 1286 |
| BigCodeBench Complete | 61.1% | 43.1% |
| SWE-bench Verified | 31% | — |
| Aider Polyglot | 45.3% | — |
| SciCode | — | 17% |
| GSO | 0% | — |
| WeirdML | 25.1% | — |
| BigCodeBench Instruct | 51.1% | — |
| LiveBench Coding | 51.4% | — |
| CadEval | 26% | — |
| HumanEval+ | 87.2% | — |
| MBPP+ | 72.2% | — |

## Agentic & Tool Use

- GPT-4o: 20.8 (#133)
- Llama 4 Scout: 24.4 (#109)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
| GDPval | 9.9% | — |
| TheAgentCompany | 8.6% | — |
| Cybench | 12.5% | — |
| BALROG | 32.3% | — |
| LMArena Search | 1006 | — |
| METR Time Horizons | 40.8% | — |

## Reasoning

- GPT-4o: 9.4 (#338)
- Llama 4 Scout: 9.2 (#339)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| ARC-AGI-2 | 0% | 0% |
| ARC-AGI-1 | 4.5% | 0.5% |
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1281 | 1266 |
| DTBench | 64.5% | 57.9% |
| LMCA | 16.6% | 12% |
| Epoch Capabilities Index | 128.97 | 129.64 |
| ForecastBench | 57.7 | 57.5 |
| SimpleBench | 17.8% | — |
| Kagi LLM Benchmark | — | 36.9% |
| Chess Puzzles | 13% | — |
| EnigmaEval | 0.8% | — |
| LiveBench Reasoning | 55.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LiveBench | 55.3% | — |

## Math

- GPT-4o: 10.2 (#303)
- Llama 4 Scout: 18.4 (#280)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.4% | 7.8% |
| Omni-MATH | 29.3% | 37.3% |
| LMArena Math | 1285 | 1286 |
| MATH Level 5 | 53.3% | 62.3% |
| FrontierMath (Feb 2025 set) | 0.3% | 0% |
| FrontierMath (Tiers 1-3) | 0.4% | — |
| LiveBench Math | 49.5% | — |

## Knowledge

- GPT-4o: 28.8 (#235)
- Llama 4 Scout: 31.8 (#208)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 49.2% | 51.8% |
| MMLU-Pro | 71.3% | 74.2% |
| Vectara Hallucination Rate | 9.6% | 7.7% |
| GPQA (HELM) | 52% | 50.7% |
| LMArena Expert | 1250 | 1236 |
| Humanity's Last Exam | 2.7% | — |
| SimpleQA Verified | 26% | — |
| Confabulations | 15.3% | — |
| MMLU | 88.1% | — |

## Multimodal

- GPT-4o: 33.9 (#85)
- Llama 4 Scout: 31.6 (#98)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1137 | 1118 |
| Video-MME | 71.9% | — |
| GeoBench | 71% | — |
| VPCT | 40% | — |
| ScienceQA | 88.5% | — |
| SpatialViz-Bench | — | 34.2% |

## Multilingual

- GPT-4o: 43.4 (#181)
- Llama 4 Scout: 41.3 (#207)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1283 | 1253 |
| LMArena Chinese | 1277 | 1256 |
| LMArena French | 1303 | 1283 |
| LMArena German | 1282 | 1274 |
| LMArena Japanese | 1257 | 1209 |
| LMArena Korean | 1234 | 1207 |
| LMArena Russian | 1286 | 1263 |
| LMArena Spanish | 1292 | 1277 |

## Instruction Following

- GPT-4o: 66.8 (#202)
- Llama 4 Scout: 66.0 (#212)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| IFEval | 81.7% | 81.8% |
| LMArena Instruction Following | 1278 | 1248 |
| LiveBench Instruction Following | 68.6% | — |

## Long Context

- GPT-4o: 39.4 (#174)
- Llama 4 Scout: 27.5 (#289)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | 66.7% | 36% |
| LMArena Longer Query | 1289 | 1265 |

## Writing & Preference

- GPT-4o: 52.8 (#160)
- Llama 4 Scout: 37.1 (#256)

| Benchmark | GPT-4o | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1300 | 1279 |
| LMArena Creative Writing | 1291 | 1249 |
| WildBench | 82.8% | 78% |
| LMArena Multi-Turn | 1302 | 1281 |
| Short-Story Creative Writing | 81.8% | — |
| EQ-Bench Creative Writing | — | 783 |
| LiveBench Language | 47.6% | — |

## FAQ

### Is GPT-4o better than Llama 4 Scout?

GPT-4o is the stronger model overall, scoring 28.5 to 27.4 on the Noometry Index. Llama 4 Scout costs 29× less per token, which makes it the better buy when GPT-4o's lead doesn't matter for your workload.

### Which is cheaper, GPT-4o 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; GPT-4o lists at $2.50 and $10.

### Is GPT-4o or Llama 4 Scout better for coding?

GPT-4o scores higher on coding benchmarks: 25.1 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do GPT-4o and Llama 4 Scout share?

38 benchmarks have published results for both models. GPT-4o has 72 scored results on Noometry and Llama 4 Scout has 43.