Llama 4 Scout vs Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 7.5 to 6.5, and Qwen3 30B A3B Instruct 2507 costs 1.7x less per output token ($0.30 vs $0.50 per million). Updated October 22, 2026; 45 benchmarks have a result for both.
Llama 4 Scout or Qwen3 30B A3B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama 4 Scout for a larger context window (1.31M against 262K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or SciCode, where it leads.
- Shared results
- 45
- Llama 4 Scout only
- 37
- Qwen3 30B A3B Instruct 2507 only
- 0
- 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
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads, 7.5 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
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 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B Instruct 2507
Llama 4 Scout $0.0004, Qwen3 30B A3B Instruct 2507 $0.0002 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
- Llama 4 Scout not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Math, 39.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: Llama 4 Scout 7.8% against Qwen3 30B A3B Instruct 2507 62.2%, 54.4 points apart on a 0 to 100 scale.
- Output price
- Llama 4 Scout $0.50 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 1.7x apart.
- Context window
- Llama 4 Scout takes 1.31M tokens, Qwen3 30B A3B Instruct 2507 262K.
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 | Llama 4 Scout | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 5 | ||
| Knowledge | 0 | 5 | ||
| General | 0 | 21 | ||
| All shared boards | 0 | 45 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| SWE-bench Verified | 9.1% | Not measured | Only Llama 4 Scout measured |
| AA Coding Index | 8.2 | Not measured | Only Llama 4 Scout measured |
| LiveCodeBench (Vals AI) | 38.5% | Not measured | Only Llama 4 Scout measured |
| LiveCodeBench (Artificial Analysis run) | 29.9% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| SciCode | 21.3% | 33.0% | Qwen3 30B A3B Instruct 2507 |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | 6.1% | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: coding | 1286 | 1416 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: software and IT | 1286 | 1417 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.5 | 7.5 | Qwen3 30B A3B Instruct 2507 |
| Epoch Capabilities Index | 129.6 | Not measured | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.5 | Not measured | Only Llama 4 Scout measured |
| τ²-Bench Telecom | 15.5% | 28.1% | Qwen3 30B A3B Instruct 2507 |
| Berkeley Function Calling Leaderboard (BFCL) | 28.1% | 41.4% | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond | 47.0% | Not measured | Only Llama 4 Scout measured |
| MMMU Pro (Vals AI) | 58.8% | Not measured | Only Llama 4 Scout measured |
| GPQA Diamond (Artificial Analysis run) | 58.7% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | 10.3% | Qwen3 30B A3B Instruct 2507 |
| GPQA Diamond (Epoch AI run) | 51.8% | 55.6% | Qwen3 30B A3B Instruct 2507 |
| ARC-AGI | 0.5% | Not measured | Only Llama 4 Scout measured |
| ARC-AGI-2 | 0.0% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: hard prompts | 1266 | 1398 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: expert | 1235 | 1397 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: hard prompts in English | 1293 | 1406 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision: diagrams | 1125 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: homework | 1148 | Not measured | Only Llama 4 Scout measured |
| Kagi LLM Benchmark | 36.9% | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AIME | 19.0% | Not measured | Only Llama 4 Scout measured |
| MATH 500 (Vals AI) | 79.2% | Not measured | Only Llama 4 Scout measured |
| MGSM (Vals AI) | 88.0% | Not measured | Only Llama 4 Scout measured |
| AA Math Index | 14.0 | 66.3 | Qwen3 30B A3B Instruct 2507 |
| AIME 2025 (Artificial Analysis run) | 14.0% | 66.3% | Qwen3 30B A3B Instruct 2507 |
| OTIS Mock AIME | 7.8% | 62.2% | Qwen3 30B A3B Instruct 2507 |
| MATH level 5 | 62.3% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: math | 1287 | 1394 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: mathematical work | 1286 | 1411 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro | 69.6% | Not measured | Only Llama 4 Scout measured |
| LegalBench (Vals AI) | 72.0% | Not measured | Only Llama 4 Scout measured |
| CorpFin (Vals AI) | 46.8% | Not measured | Only Llama 4 Scout measured |
| TaxEval (Vals AI) | 55.2% | Not measured | Only Llama 4 Scout measured |
| MortgageTax (Vals AI) | 57.8% | Not measured | Only Llama 4 Scout measured |
| MedQA (Vals AI) | 50.9% | Not measured | Only Llama 4 Scout measured |
| MedCode (Vals AI) | 23.3% | Not measured | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | 75.2% | 80.5% | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: science | 1278 | 1393 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: medicine and healthcare | 1275 | 1392 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: legal and government | 1285 | 1387 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: business and finance | 1257 | 1389 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 750 | Not measured | Only Llama 4 Scout measured |
| Design Arena: UI components | 765 | Not measured | Only Llama 4 Scout measured |
| Design Arena: game dev | 772 | Not measured | Only Llama 4 Scout measured |
| Design Arena: data viz | 896 | Not measured | Only Llama 4 Scout measured |
| Design Arena: all code categories | 789 | Not measured | 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 index021
| Benchmark | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 34.8% | Not measured | Only Llama 4 Scout measured |
| MedScribe (Vals AI) | 50.6% | Not measured | Only Llama 4 Scout measured |
| IFBench | 39.5% | 50.7% | Qwen3 30B A3B Instruct 2507 |
| Long context reasoning (AA-LCR) | 27.7% | 61.3% | Qwen3 30B A3B Instruct 2507 |
| DTBench | 57.9% | 67.2% | Qwen3 30B A3B Instruct 2507 |
| LMCA | 12.0% | 22.4% | Qwen3 30B A3B Instruct 2507 |
| Fiction.LiveBench | 36.0% | Not measured | Only Llama 4 Scout measured |
| LMArena Text | 1279 | 1384 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: instruction following | 1248 | 1363 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: creative writing | 1249 | 1317 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision | 1118 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: English | 1304 | 1391 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: non-English | 1252 | 1372 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Chinese | 1255 | 1432 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: German | 1273 | 1379 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Japanese | 1206 | 1337 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Korean | 1207 | 1330 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: French | 1283 | 1419 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Spanish | 1278 | 1404 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Russian | 1263 | 1369 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Polish | 1265 | 1353 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: multi-turn | 1280 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: longer queries | 1265 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: writing and language | 1269 | 1336 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: entertainment and media | 1242 | 1334 | Qwen3 30B A3B Instruct 2507 |
| LMArena Vision: English | 1143 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: Chinese | 1106 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: reading text | 1117 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: humor | 1102 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: creative writing | 1126 | Not measured | 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 | Llama 4 Scout | Qwen3 30B A3B Instruct 2507 | 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
Qwen3 30B A3B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 30B A3B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 30B A3B Instruct 2507 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 | Meta Llama 4 Scout | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Meta Llama | Qwen |
| Weights | Open weights | Open weights |
| Released | April 5, 2025 | July 29, 2025 |
| Context window | 1.31M | 262K |
| Input $/Mtok | $0.175 | $0.09 |
| Output $/Mtok | $0.50 | $0.30 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $1.276 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 4 Scout better than Qwen3 30B A3B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 4 Scout for a larger context window (1.31M against 262K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or SciCode, where it leads.
Which is cheaper, Llama 4 Scout or Qwen3 30B A3B Instruct 2507?
Llama 4 Scout costs $0.175 per million input tokens and $0.50 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for Llama 4 Scout only.
Which has the bigger context window, Llama 4 Scout or Qwen3 30B A3B Instruct 2507?
Llama 4 Scout, with 1.31M tokens against 262K.
How many benchmarks is the Llama 4 Scout vs Qwen3 30B A3B Instruct 2507 comparison based on?
45 benchmarks have a result for both models as of October 22, 2026. Llama 4 Scout's coding index rests on 0 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.