Nova Premier 1.0 vs Llama 4 Scout
Nova Premier 1.0 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 9.2 to 6.5, and Llama 4 Scout costs 25.0x less per output token ($0.50 vs $12.50 per million). Updated October 21, 2026; 13 benchmarks have a result for both.
Nova Premier 1.0 or Llama 4 Scout: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for work measured by GPQA Diamond (Artificial Analysis run) or MMLU Pro (Artificial Analysis run), where it leads.
- Shared results
- 13
- Nova Premier 1.0 only
- 1
- Llama 4 Scout only
- 69
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Nova Premier 1.0
Nova Premier 1.0 leads, 9.2 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Llama 4 Scout has a AA Agentic Index result, 0.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Llama 4 Scout has a GPQA Diamond result, 47.0%.
Directional only
Math
AIME
No call
Only Llama 4 Scout has a AIME result, 19.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Llama 4 Scout has a MMLU Pro result, 69.6%.
Directional only
Web design
Design Arena: websites
Nova Premier 1.0
Nova Premier 1.0 leads, 835 against 750.
Same board, both measured
Long documents
Listed context window
Llama 4 Scout
Llama 4 Scout takes 1.31M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Scout
Nova Premier 1.0 $0.0088, Llama 4 Scout $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Llama 4 Scout has the number, $1.276.
Directional only
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, Llama 4 Scout not benchmarked.
- Widest category
- Agentic work, 22.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Premier 1.0 38.3% against Llama 4 Scout 15.5%, 22.8 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against Llama 4 Scout $0.50 per million output tokens, 25.0x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, Llama 4 Scout 1.31M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Nova Premier 1.0 | Bars | Llama 4 Scout | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 0 | 1 | ||
| Web design | 1 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 10 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 9.1% | Only Llama 4 Scout measured |
| AA Coding Index | Not measured | 8.2 | Only Llama 4 Scout measured |
| LiveCodeBench (Vals AI) | Not measured | 38.5% | Only Llama 4 Scout measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | 29.9% | Nova Premier 1.0 |
| SciCode | Not measured | 21.3% | Only Llama 4 Scout measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | 1.5% | Nova Premier 1.0 |
| ALE-Bench | 147.4 | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: coding | Not measured | 1286 | Only Llama 4 Scout measured |
| LMArena Text: software and IT | Not measured | 1286 | Only Llama 4 Scout measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 6.5 | Nova Premier 1.0 |
| Epoch Capabilities Index | Not measured | 129.6 | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.5 | Only Llama 4 Scout measured |
| τ²-Bench Telecom | 38.3% | 15.5% | Nova Premier 1.0 |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 28.1% | Only Llama 4 Scout measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.0% | Only Llama 4 Scout measured |
| MMMU Pro (Vals AI) | Not measured | 58.8% | Only Llama 4 Scout measured |
| GPQA Diamond (Artificial Analysis run) | 56.9% | 58.7% | Llama 4 Scout |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 3.8% | Nova Premier 1.0 |
| GPQA Diamond (Epoch AI run) | Not measured | 51.8% | Only Llama 4 Scout measured |
| ARC-AGI | Not measured | 0.5% | Only Llama 4 Scout measured |
| ARC-AGI-2 | Not measured | 0.0% | Only Llama 4 Scout measured |
| LMArena Text: hard prompts | Not measured | 1266 | Only Llama 4 Scout measured |
| LMArena Text: expert | Not measured | 1235 | Only Llama 4 Scout measured |
| LMArena Text: hard prompts in English | Not measured | 1293 | Only Llama 4 Scout measured |
| LMArena Vision: diagrams | Not measured | 1125 | Only Llama 4 Scout measured |
| LMArena Vision: homework | Not measured | 1148 | Only Llama 4 Scout measured |
| Kagi LLM Benchmark | 44.8% | 36.9% | Nova Premier 1.0 |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| AIME | Not measured | 19.0% | Only Llama 4 Scout measured |
| MATH 500 (Vals AI) | Not measured | 79.2% | Only Llama 4 Scout measured |
| MGSM (Vals AI) | Not measured | 88.0% | Only Llama 4 Scout measured |
| AA Math Index | 17.3 | 14.0 | Nova Premier 1.0 |
| AIME 2025 (Artificial Analysis run) | 17.3% | 14.0% | Nova Premier 1.0 |
| OTIS Mock AIME | Not measured | 7.8% | Only Llama 4 Scout measured |
| MATH level 5 | Not measured | 62.3% | Only Llama 4 Scout measured |
| LMArena Text: math | Not measured | 1287 | Only Llama 4 Scout measured |
| LMArena Text: mathematical work | Not measured | 1286 | Only Llama 4 Scout measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.6% | Only Llama 4 Scout measured |
| LegalBench (Vals AI) | Not measured | 72.0% | Only Llama 4 Scout measured |
| CorpFin (Vals AI) | Not measured | 46.8% | Only Llama 4 Scout measured |
| TaxEval (Vals AI) | Not measured | 55.2% | Only Llama 4 Scout measured |
| MortgageTax (Vals AI) | Not measured | 57.8% | Only Llama 4 Scout measured |
| MedQA (Vals AI) | Not measured | 50.9% | Only Llama 4 Scout measured |
| MedCode (Vals AI) | Not measured | 23.3% | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | 73.3% | 75.2% | Llama 4 Scout |
| LMArena Text: science | Not measured | 1278 | Only Llama 4 Scout measured |
| LMArena Text: medicine and healthcare | Not measured | 1275 | Only Llama 4 Scout measured |
| LMArena Text: legal and government | Not measured | 1285 | Only Llama 4 Scout measured |
| LMArena Text: business and finance | Not measured | 1257 | Only Llama 4 Scout measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 750 | Nova Premier 1.0 |
| Design Arena: UI components | Not measured | 768 | Only Llama 4 Scout measured |
| Design Arena: game dev | Not measured | 773 | Only Llama 4 Scout measured |
| Design Arena: data viz | Not measured | 896 | Only Llama 4 Scout measured |
| Design Arena: all code categories | Not measured | 790 | Only Llama 4 Scout measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 34.8% | Only Llama 4 Scout measured |
| MedScribe (Vals AI) | Not measured | 50.6% | Only Llama 4 Scout measured |
| IFBench | 36.2% | 39.5% | Llama 4 Scout |
| Long context reasoning (AA-LCR) | 34.3% | 27.7% | Nova Premier 1.0 |
| DTBench | Not measured | 57.9% | Only Llama 4 Scout measured |
| LMCA | Not measured | 12.0% | Only Llama 4 Scout measured |
| Fiction.LiveBench | Not measured | 36.0% | Only Llama 4 Scout measured |
| LMArena Text | Not measured | 1279 | Only Llama 4 Scout measured |
| LMArena Text: instruction following | Not measured | 1248 | Only Llama 4 Scout measured |
| LMArena Text: creative writing | Not measured | 1249 | Only Llama 4 Scout measured |
| LMArena Vision | Not measured | 1118 | Only Llama 4 Scout measured |
| LMArena Text: English | Not measured | 1304 | Only Llama 4 Scout measured |
| LMArena Text: non-English | Not measured | 1252 | Only Llama 4 Scout measured |
| LMArena Text: Chinese | Not measured | 1255 | Only Llama 4 Scout measured |
| LMArena Text: German | Not measured | 1273 | Only Llama 4 Scout measured |
| LMArena Text: Japanese | Not measured | 1206 | Only Llama 4 Scout measured |
| LMArena Text: Korean | Not measured | 1207 | Only Llama 4 Scout measured |
| LMArena Text: French | Not measured | 1283 | Only Llama 4 Scout measured |
| LMArena Text: Spanish | Not measured | 1278 | Only Llama 4 Scout measured |
| LMArena Text: Russian | Not measured | 1263 | Only Llama 4 Scout measured |
| LMArena Text: Polish | Not measured | 1265 | Only Llama 4 Scout measured |
| LMArena Text: multi-turn | Not measured | 1280 | Only Llama 4 Scout measured |
| LMArena Text: longer queries | Not measured | 1265 | Only Llama 4 Scout measured |
| LMArena Text: writing and language | Not measured | 1269 | Only Llama 4 Scout measured |
| LMArena Text: entertainment and media | Not measured | 1242 | Only Llama 4 Scout measured |
| LMArena Vision: English | Not measured | 1143 | Only Llama 4 Scout measured |
| LMArena Vision: Chinese | Not measured | 1106 | Only Llama 4 Scout measured |
| LMArena Vision: reading text | Not measured | 1117 | Only Llama 4 Scout measured |
| LMArena Vision: humor | Not measured | 1102 | Only Llama 4 Scout measured |
| LMArena Vision: creative writing | Not measured | 1126 | Only Llama 4 Scout measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | Llama 4 Scout | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Llama 4 Scout costs less
Repository review
50K input + 3K output tokens
Llama 4 Scout costs less
Agent loop
200K input + 10K output tokens
Llama 4 Scout costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Amazon Nova Premier 1.0 | Meta Llama 4 Scout |
|---|---|---|
| Maker | Amazon | Meta Llama |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | April 5, 2025 |
| Context window | 1M | 1.31M |
| Input $/Mtok | $2.50 | $0.175 |
| Output $/Mtok | $12.50 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | $1.276 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than Llama 4 Scout for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for work measured by GPQA Diamond (Artificial Analysis run) or MMLU Pro (Artificial Analysis run), where it leads.
Which is cheaper, Nova Premier 1.0 or Llama 4 Scout?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; Llama 4 Scout costs $0.175 and $0.50. Cost per solved task is known for Llama 4 Scout only.
Which has the bigger context window, Nova Premier 1.0 or Llama 4 Scout?
Llama 4 Scout, with 1.31M tokens against 1M.
How many benchmarks is the Nova Premier 1.0 vs Llama 4 Scout comparison based on?
13 benchmarks have a result for both models as of October 21, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and Llama 4 Scout's on 0. Where only one model has a result, the page says so instead of naming a winner.