Model comparison
GPT-6 Luna vs Llama 4 Scout
GPT-6 Luna is the stronger model overall, scoring 45.1 to 27.4 on the Noometry Index.
Last verified . 13 shared benchmarks.
MetaSummary
- They share 13 benchmarks with published results for both. GPT-6 Luna scores higher in 9 categories and Llama 4 Scout in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Luna leads 54.7 to 19.9.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Luna | Llama 4 Scout | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 45.1 | 27.4 |
| Released | 2026-09-22 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $0.10 | $0.10 |
| Output $ / M tokens | $0.50 | $0.30 |
| Results tracked | 18 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Luna leads
GPT-6 Luna: 54.7 (#24), Llama 4 Scout: 19.9 (#334)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1448 | 1286 |
| DeepSWE | 66.6% | — |
| FrontierCode | 42.4% | — |
| SWE-bench Verified (bash only) | — | 9.1% |
| LMArena WebDev | 1583 | — |
| SciCode | — | 17% |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Not comparable
GPT-6 Luna: —, Llama 4 Scout: 24.4 (#109)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning GPT-6 Luna leads
GPT-6 Luna: 31.7 (#68), Llama 4 Scout: 9.2 (#339)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1266 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| NYT Connections (extended) | 68.7% | — |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Epoch Capabilities Index | — | 129.64 |
| ForecastBench | — | 57.5 |
Math GPT-6 Luna leads
GPT-6 Luna: 35.6 (#140), Llama 4 Scout: 18.4 (#280)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Math | 1396 | 1286 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge GPT-6 Luna leads
GPT-6 Luna: 40.1 (#110), Llama 4 Scout: 31.8 (#208)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Expert | 1458 | 1236 |
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
Multimodal GPT-6 Luna leads
GPT-6 Luna: 42.0 (#27), Llama 4 Scout: 31.6 (#98)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| Furniture Assembly | 44.2% | — |
| SpatialViz-Bench | — | 34.2% |
Multilingual GPT-6 Luna leads
GPT-6 Luna: 51.0 (#111), Llama 4 Scout: 41.3 (#207)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1390 | 1253 |
| LMArena Chinese | 1425 | 1256 |
| LMArena Russian | 1392 | 1263 |
| LMArena Spanish | 1416 | 1277 |
| LMArena French | — | 1283 |
| LMArena German | — | 1274 |
| LMArena Japanese | — | 1209 |
| LMArena Korean | — | 1207 |
Instruction Following GPT-6 Luna leads
GPT-6 Luna: 74.7 (#85), Llama 4 Scout: 66.0 (#212)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1414 | 1248 |
| IFEval | — | 81.8% |
Long Context GPT-6 Luna leads
GPT-6 Luna: 43.3 (#95), Llama 4 Scout: 27.5 (#289)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1417 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference GPT-6 Luna leads
GPT-6 Luna: 58.4 (#115), Llama 4 Scout: 37.1 (#256)
| Benchmark | GPT-6 Luna | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1392 | 1279 |
| LMArena Creative Writing | 1357 | 1249 |
| LMArena Multi-Turn | 1400 | 1281 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
Frequently asked questions
Is GPT-6 Luna better than Llama 4 Scout?
GPT-6 Luna is the stronger model overall, scoring 45.1 to 27.4 on the Noometry Index.
Which is cheaper, GPT-6 Luna 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-6 Luna lists at $0.10 and $0.50.
Is GPT-6 Luna or Llama 4 Scout better for coding?
GPT-6 Luna scores higher on coding benchmarks: 54.7 versus 19.9 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 128K.
How many benchmarks do GPT-6 Luna and Llama 4 Scout share?
13 benchmarks have published results for both models. GPT-6 Luna has 18 scored results on Noometry and Llama 4 Scout has 43.