Model comparison
Amazon Nova Pro vs Llama 4 Scout
Amazon Nova Pro is the stronger model overall, scoring 31.0 to 27.7 on the Noometry Index. Llama 4 Scout costs 9.3× less per token, which makes it the better buy when Amazon Nova Pro's lead doesn't matter for your workload.
Last verified . 26 shared benchmarks.
MetaSummary
- They share 26 benchmarks with published results for both. Amazon Nova Pro scores higher in 5 categories and Llama 4 Scout in 5 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in coding, where Amazon Nova Pro leads 35.1 to 20.2.
- The biggest single-benchmark swing is Omni-MATH: 24.2% for Amazon Nova Pro and 37.3% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.80 / $3.20 for Amazon Nova Pro.
- Amazon Nova Pro accepts more context: 300K tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Pro | Llama 4 Scout | |
|---|---|---|
| Provider | Amazon | Meta |
| Noometry Index | 31.0 | 27.7 |
| Released | 2024-12-03 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 300K | 128K |
| Max output | 10K | 4K |
| Input $ / M tokens | $0.80 | $0.10 |
| Output $ / M tokens | $3.20 | $0.30 |
| Results tracked | 38 | 43 |
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Category by category
Coding Amazon Nova Pro leads
Amazon Nova Pro: 35.1 (#229), Llama 4 Scout: 20.2 (#339)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1270 | 1286 |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| LiveBench Coding | 38.1% | — |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Llama 4 Scout leads
Amazon Nova Pro: 16.7 (#147), Llama 4 Scout: 24.6 (#119)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25% | 28.1% |
| TheAgentCompany | 1.7% | — |
Reasoning Amazon Nova Pro leads
Amazon Nova Pro: 20.0 (#243), Llama 4 Scout: 9.1 (#345)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1246 | 1266 |
| Epoch Capabilities Index | 123.8 | 129.64 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| LiveBench Reasoning | 32.6% | — |
| DTBench | — | 57.9% |
| LiveBench Data Analysis | 48.3% | — |
| LMCA | — | 12% |
| ForecastBench | — | 57.5 |
| LiveBench | 43.5% | — |
Math Amazon Nova Pro leads
Amazon Nova Pro: 28.5 (#243), Llama 4 Scout: 19.6 (#286)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| Omni-MATH | 24.2% | 37.3% |
| LMArena Math | 1252 | 1287 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| LiveBench Math | 38% | — |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Llama 4 Scout leads
Amazon Nova Pro: 27.4 (#250), Llama 4 Scout: 31.9 (#217)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| MMLU-Pro | 67.3% | 74.2% |
| Vectara Hallucination Rate | 5.1% | 7.7% |
| GPQA (HELM) | 44.6% | 50.7% |
| LMArena Expert | 1211 | 1235 |
| GPQA Diamond | — | 51.8% |
| Humanity's Last Exam | 4.4% | — |
| Confabulations | 30.1% | — |
| MMLU | 82% | — |
Multimodal Llama 4 Scout leads
Amazon Nova Pro: 25.0 (#126), Llama 4 Scout: 32.2 (#102)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 980 | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Llama 4 Scout leads
Amazon Nova Pro: 39.7 (#223), Llama 4 Scout: 41.0 (#212)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1234 | 1252 |
| LMArena Chinese | 1244 | 1255 |
| LMArena French | 1271 | 1282 |
| LMArena German | 1243 | 1272 |
| LMArena Japanese | 1200 | 1206 |
| LMArena Korean | 1203 | 1207 |
| LMArena Russian | 1240 | 1263 |
| LMArena Spanish | 1182 | 1278 |
Instruction Following Too close to call
Amazon Nova Pro: 64.9 (#226), Llama 4 Scout: 65.8 (#217)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| IFEval | 81.5% | 81.8% |
| LMArena Instruction Following | 1235 | 1248 |
| LiveBench Instruction Following | 67.1% | — |
Long Context Amazon Nova Pro leads
Amazon Nova Pro: 38.1 (#205), Llama 4 Scout: 27.5 (#294)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1255 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Amazon Nova Pro leads
Amazon Nova Pro: 43.9 (#226), Llama 4 Scout: 37.0 (#261)
| Benchmark | Amazon Nova Pro | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1259 | 1279 |
| LMArena Creative Writing | 1212 | 1249 |
| WildBench | 77.7% | 78% |
| LMArena Multi-Turn | 1246 | 1280 |
| Short-Story Creative Writing | 60.5% | — |
| EQ-Bench Creative Writing | — | 783 |
| LiveBench Language | 37% | — |
Frequently asked questions
Is Amazon Nova Pro better than Llama 4 Scout?
Amazon Nova Pro is the stronger model overall, scoring 31.0 to 27.7 on the Noometry Index. Llama 4 Scout costs 9.3× less per token, which makes it the better buy when Amazon Nova Pro's lead doesn't matter for your workload.
Which is cheaper, Amazon Nova Pro 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; Amazon Nova Pro lists at $0.80 and $3.20.
Is Amazon Nova Pro or Llama 4 Scout better for coding?
Amazon Nova Pro scores higher on coding benchmarks: 35.1 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Amazon Nova Pro does, with 300K tokens against 128K.
How many benchmarks do Amazon Nova Pro and Llama 4 Scout share?
26 benchmarks have published results for both models. Amazon Nova Pro has 38 scored results on Noometry and Llama 4 Scout has 43.