Granite 4.0 Micro vs Llama 4 Scout
Llama 4 Scout leads Granite 4.0 Micro on the Artificial Analysis Intelligence Index, 6.5 to 5.1, and Granite 4.0 Micro costs 4.5x less per output token ($0.112 vs $0.50 per million). Updated October 23, 2026; 13 benchmarks have a result for both.
Granite 4.0 Micro or Llama 4 Scout: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Granite 4.0 Micro for output tokens 4.5x cheaper ($0.112 vs $0.50 per million) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 13
- Granite 4.0 Micro only
- 0
- Llama 4 Scout only
- 69
- Like-for-like categories
- 7 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
Llama 4 Scout
Llama 4 Scout leads, 6.5 against 5.1.
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
No call
Only Llama 4 Scout has a Design Arena: websites result, 750.
Directional only
Long documents
Listed context window
Llama 4 Scout
Llama 4 Scout takes 1.31M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
Granite 4.0 Micro $0.0001, 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
- Granite 4.0 Micro not benchmarked, Llama 4 Scout not benchmarked.
- Widest category
- Knowledge, 30.5 points apart on average over 1 shared benchmark.
- Widest single gap
- MMLU Pro (Artificial Analysis run): Granite 4.0 Micro 44.7% against Llama 4 Scout 75.2%, 30.5 points apart on a 0 to 100 scale.
- Output price
- Granite 4.0 Micro $0.112 against Llama 4 Scout $0.50 per million output tokens, 4.5x apart.
- Context window
- Granite 4.0 Micro takes 131K 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 | Granite 4.0 Micro | Bars | Llama 4 Scout | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | 1 tie | |
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 1 | 11 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Granite 4.0 Micro | 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) | 18.0% | 29.9% | Llama 4 Scout |
| SciCode | Not measured | 21.3% | Only Llama 4 Scout measured |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | 1.5% | Tie |
| 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 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.1 | 6.5 | Llama 4 Scout |
| Epoch Capabilities Index | Not measured | 129.6 | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.5 | Only Llama 4 Scout measured |
| τ²-Bench Telecom | 12.6% | 15.5% | Llama 4 Scout |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 28.1% | Only Llama 4 Scout measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Granite 4.0 Micro | 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) | 33.6% | 58.7% | Llama 4 Scout |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 3.8% | Granite 4.0 Micro |
| GPQA Diamond (Epoch AI run) | 28.3% | 51.8% | Llama 4 Scout |
| 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 | Not measured | 36.9% | Only Llama 4 Scout measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Granite 4.0 Micro | 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 | 6.0 | 14.0 | Llama 4 Scout |
| AIME 2025 (Artificial Analysis run) | 6.0% | 14.0% | Llama 4 Scout |
| OTIS Mock AIME | 2.8% | 7.8% | Llama 4 Scout |
| 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 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | 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) | 44.7% | 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 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Granite 4.0 Micro | Llama 4 Scout | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 750 | Only Llama 4 Scout measured |
| Design Arena: UI components | Not measured | 765 | Only Llama 4 Scout measured |
| Design Arena: game dev | Not measured | 772 | Only Llama 4 Scout measured |
| Design Arena: data viz | Not measured | 896 | Only Llama 4 Scout measured |
| Design Arena: all code categories | Not measured | 789 | 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 index02
| Benchmark | Granite 4.0 Micro | 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 | 24.8% | 39.5% | Llama 4 Scout |
| Long context reasoning (AA-LCR) | 7.0% | 27.7% | Llama 4 Scout |
| 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 | 1272 | 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 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Granite 4.0 Micro | 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
Granite 4.0 Micro costs less
Repository review
50K input + 3K output tokens
Granite 4.0 Micro costs less
Agent loop
200K input + 10K output tokens
Granite 4.0 Micro 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 | IBM Granite 4.0 Micro | Meta Llama 4 Scout |
|---|---|---|
| Maker | IBM Granite | Meta Llama |
| Weights | Open weights | Open weights |
| Released | October 20, 2025 | April 5, 2025 |
| Context window | 131K | 1.31M |
| Input $/Mtok | $0.017 | $0.175 |
| Output $/Mtok | $0.112 | $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 Granite 4.0 Micro better than Llama 4 Scout for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Granite 4.0 Micro for output tokens 4.5x cheaper ($0.112 vs $0.50 per million) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, Granite 4.0 Micro or Llama 4 Scout?
Granite 4.0 Micro costs $0.017 per million input tokens and $0.112 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, Granite 4.0 Micro or Llama 4 Scout?
Llama 4 Scout, with 1.31M tokens against 131K.
How many benchmarks is the Granite 4.0 Micro vs Llama 4 Scout comparison based on?
13 benchmarks have a result for both models as of October 23, 2026. Granite 4.0 Micro'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.