Model comparison
INTELLECT-1 vs Llama 4 Scout
Llama 4 Scout has enough public results to be ranked (#330); INTELLECT-1 does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
Hugging Face
MetaSummary
- They share 1 benchmark with published results for both.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| INTELLECT-1 | Llama 4 Scout | |
|---|---|---|
| Provider | Hugging Face | Meta |
| Noometry Index | — | 27.7 |
| Released | 2024-11-29 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.30 |
| Results tracked | 7 | 43 |
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Category by category
Coding Not comparable
INTELLECT-1: —, Llama 4 Scout: 20.2 (#339)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| LMArena Coding | — | 1286 |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Not comparable
INTELLECT-1: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Not comparable
INTELLECT-1: —, Llama 4 Scout: 9.1 (#345)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| Epoch Capabilities Index | 100.86 | 129.64 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1266 |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| BIG-Bench Hard | 34.9% | — |
| ForecastBench | — | 57.5 |
| HellaSwag | 71.4% | — |
| WinoGrande | 65.8% | — |
Math Not comparable
INTELLECT-1: —, Llama 4 Scout: 19.6 (#286)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| LMArena Math | — | 1287 |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
| GSM8K | 38.6% | — |
Knowledge Not comparable
INTELLECT-1: —, Llama 4 Scout: 31.9 (#217)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1235 |
| ARC (AI2) Challenge | 54.5% | — |
| MMLU | 49.9% | — |
Multimodal Not comparable
INTELLECT-1: —, Llama 4 Scout: 32.2 (#102)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Not comparable
INTELLECT-1: —, Llama 4 Scout: 41.0 (#212)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | — | 1252 |
| LMArena Chinese | — | 1255 |
| LMArena French | — | 1282 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1206 |
| LMArena Korean | — | 1207 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1278 |
Instruction Following Not comparable
INTELLECT-1: —, Llama 4 Scout: 65.8 (#217)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| IFEval | — | 81.8% |
| LMArena Instruction Following | — | 1248 |
Long Context Not comparable
INTELLECT-1: —, Llama 4 Scout: 27.5 (#294)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | — | 36% |
| LMArena Longer Query | — | 1265 |
Writing & Preference Not comparable
INTELLECT-1: —, Llama 4 Scout: 37.0 (#261)
| Benchmark | INTELLECT-1 | Llama 4 Scout |
|---|---|---|
| LMArena Text | — | 1279 |
| LMArena Creative Writing | — | 1249 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
| LMArena Multi-Turn | — | 1280 |
Frequently asked questions
Is INTELLECT-1 better than Llama 4 Scout?
Llama 4 Scout has enough public results to be ranked (#330); INTELLECT-1 does not yet, so treat this comparison as directional.
How many benchmarks do INTELLECT-1 and Llama 4 Scout share?
1 benchmark has published results for both models. INTELLECT-1 has 7 scored results on Noometry and Llama 4 Scout has 43.