Model comparison
Amazon Nova Experimental Chat 26 01 10 vs Llama 4 Scout
Amazon Nova Experimental Chat 26 01 10 is the stronger model overall, scoring 42.8 to 27.7 on the Noometry Index.
Last verified . 13 shared benchmarks.
MetaSummary
- They share 13 benchmarks with published results for both. Amazon Nova Experimental Chat 26 01 10 scores higher in 8 categories and Llama 4 Scout in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where Amazon Nova Experimental Chat 26 01 10 leads 42.7 to 20.2.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout | |
|---|---|---|
| Provider | Amazon | Meta |
| Noometry Index | 42.8 | 27.7 |
| Released | — | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.30 |
| Results tracked | 13 | 43 |
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Category by category
Coding Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 42.7 (#96), Llama 4 Scout: 20.2 (#339)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1447 | 1286 |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Not comparable
Amazon Nova Experimental Chat 26 01 10: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 28.9 (#98), Llama 4 Scout: 9.1 (#345)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1266 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Epoch Capabilities Index | — | 129.64 |
| ForecastBench | — | 57.5 |
Math Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 38.5 (#136), Llama 4 Scout: 19.6 (#286)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Math | 1404 | 1287 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 40.3 (#120), Llama 4 Scout: 31.9 (#217)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Expert | 1444 | 1235 |
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
Multimodal Not comparable
Amazon Nova Experimental Chat 26 01 10: —, Llama 4 Scout: 32.2 (#102)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 50.2 (#126), Llama 4 Scout: 41.0 (#212)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1381 | 1252 |
| LMArena Chinese | 1372 | 1255 |
| LMArena Russian | 1391 | 1263 |
| LMArena Spanish | 1390 | 1278 |
| LMArena French | — | 1282 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1206 |
| LMArena Korean | — | 1207 |
Instruction Following Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 72.9 (#126), Llama 4 Scout: 65.8 (#217)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1381 | 1248 |
| IFEval | — | 81.8% |
Long Context Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 42.7 (#119), Llama 4 Scout: 27.5 (#294)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1400 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Amazon Nova Experimental Chat 26 01 10 leads
Amazon Nova Experimental Chat 26 01 10: 57.4 (#129), Llama 4 Scout: 37.0 (#261)
| Benchmark | Amazon Nova Experimental Chat 26 01 10 | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1396 | 1279 |
| LMArena Creative Writing | 1331 | 1249 |
| LMArena Multi-Turn | 1380 | 1280 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
Frequently asked questions
Is Amazon Nova Experimental Chat 26 01 10 better than Llama 4 Scout?
Amazon Nova Experimental Chat 26 01 10 is the stronger model overall, scoring 42.8 to 27.7 on the Noometry Index.
Is Amazon Nova Experimental Chat 26 01 10 or Llama 4 Scout better for coding?
Amazon Nova Experimental Chat 26 01 10 scores higher on coding benchmarks: 42.7 versus 20.2 in the Noometry coding category.
How many benchmarks do Amazon Nova Experimental Chat 26 01 10 and Llama 4 Scout share?
13 benchmarks have published results for both models. Amazon Nova Experimental Chat 26 01 10 has 13 scored results on Noometry and Llama 4 Scout has 43.