Llama 4 Scout vs Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 45.4 to 6.5, and Llama 4 Scout costs 12.0x less per output token ($0.50 vs $6.00 per million). Updated October 22, 2026; 64 benchmarks have a result for both.
Llama 4 Scout or Qwen3.8 Max (0902): which to pick
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding.
Pick Llama 4 Scout for output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and a lower cost per solved task ($1.276 against $1.32).
- Shared results
- 64
- Llama 4 Scout only
- 18
- Qwen3.8 Max (0902) only
- 49
- 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
Only Qwen3.8 Max (0902) has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 0.5.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 47.0%.
Same board, both measured
Math
AIME
No call
Only Llama 4 Scout has a AIME result, 19.0%.
Directional only
Knowledge
MMLU Pro
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 88.6% against 69.6%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 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
Llama 4 Scout $0.0004, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Llama 4 Scout
Llama 4 Scout $1.276, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- Llama 4 Scout not benchmarked, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
- Widest category
- Web design, 63.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: Llama 4 Scout 7.8% against Qwen3.8 Max (0902) 100.0%, 92.2 points apart on a 0 to 100 scale.
- Output price
- Llama 4 Scout $0.50 against Qwen3.8 Max (0902) $6.00 per million output tokens, 12.0x apart.
- Context window
- Llama 4 Scout takes 1.31M tokens, Qwen3.8 Max (0902) 1M.
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 | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 10 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 10 | ||
| Web design | 0 | 5 | ||
| General | 0 | 28 | ||
| All shared boards | 0 | 64 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| SWE-bench Verified | 9.1% | Not measured | Only Llama 4 Scout measured |
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | Not measured | 1674 | Only Qwen3.8 Max (0902) measured |
| AA Coding Index | 8.2 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | 38.5% | 87.8% | Qwen3.8 Max (0902) |
| SWE-bench Verified (Vals AI) | Not measured | 85.6% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | Not measured | 64.7% | Only Qwen3.8 Max (0902) measured |
| Code migration (Vals AI) | Not measured | 24.0% | Only Qwen3.8 Max (0902) measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.4% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 12.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Artificial Analysis run) | 29.9% | Not measured | Only Llama 4 Scout measured |
| SciCode | 21.3% | 53.2% | Qwen3.8 Max (0902) |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | Not measured | Only Llama 4 Scout measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: coding | 1286 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1286 | 1498 | Qwen3.8 Max (0902) |
| LMArena WebDev: React | Not measured | 1692 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: HTML | Not measured | 1649 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.5 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 129.6 | 157.4 | Qwen3.8 Max (0902) |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | 0.5 | 56.0 | Qwen3.8 Max (0902) |
| Design Arena: agents building web apps | Not measured | 1300 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1305 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building mobile apps | Not measured | 1224 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1196 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1234 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1233 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 967 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 69.9% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 42.3% | Only Qwen3.8 Max (0902) measured |
| Finance Agent (Vals AI) | Not measured | 50.6% | Only Qwen3.8 Max (0902) measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only Qwen3.8 Max (0902) measured |
| Legal Research Bench (Vals AI) | Not measured | 47.6% | Only Qwen3.8 Max (0902) measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 60.1% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| τ²-Bench Telecom | 15.5% | Not measured | Only Llama 4 Scout measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Berkeley Function Calling Leaderboard (BFCL) | 28.1% | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | 47.0% | 93.7% | Qwen3.8 Max (0902) |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | 58.8% | 88.0% | Qwen3.8 Max (0902) |
| GPQA Diamond (Artificial Analysis run) | 58.7% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 51.8% | 92.7% | Qwen3.8 Max (0902) |
| ARC-AGI | 0.5% | Not measured | Only Llama 4 Scout measured |
| ARC-AGI-2 | 0.0% | Not measured | Only Llama 4 Scout measured |
| Chess puzzles | Not measured | 46.0% | Only Qwen3.8 Max (0902) measured |
| Mystery game puzzles | Not measured | 38.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts | 1266 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1235 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1293 | 1503 | Qwen3.8 Max (0902) |
| LMArena Vision: diagrams | 1125 | 1323 | Qwen3.8 Max (0902) |
| LMArena Vision: homework | 1148 | 1336 | Qwen3.8 Max (0902) |
| Kagi LLM Benchmark | 36.9% | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | 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 | Not measured | Only Llama 4 Scout measured |
| AIME 2025 (Artificial Analysis run) | 14.0% | Not measured | Only Llama 4 Scout measured |
| OTIS Mock AIME | 7.8% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | Not measured | 74.7% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| MATH level 5 | 62.3% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: math | 1287 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1286 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | 69.6% | 88.6% | Qwen3.8 Max (0902) |
| LegalBench (Vals AI) | 72.0% | 83.6% | Qwen3.8 Max (0902) |
| CorpFin (Vals AI) | 46.8% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | 55.2% | 75.5% | Qwen3.8 Max (0902) |
| MortgageTax (Vals AI) | 57.8% | 64.0% | Qwen3.8 Max (0902) |
| MedQA (Vals AI) | 50.9% | Not measured | Only Llama 4 Scout measured |
| MedCode (Vals AI) | 23.3% | 40.7% | Qwen3.8 Max (0902) |
| MMLU Pro (Artificial Analysis run) | 75.2% | Not measured | Only Llama 4 Scout measured |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | 1278 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1275 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1285 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1257 | 1480 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 750 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 765 | 1338 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 772 | 1312 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 896 | 1281 | Qwen3.8 Max (0902) |
| Design Arena: 3D | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | 789 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: ASCII art | Not measured | 1200 | Only Qwen3.8 Max (0902) measured |
| LiveBench design | Not measured | 78.6% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index028
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | 34.8% | 51.2% | Qwen3.8 Max (0902) |
| MedScribe (Vals AI) | 50.6% | 85.0% | Qwen3.8 Max (0902) |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 39.5% | Not measured | Only Llama 4 Scout measured |
| Long context reasoning (AA-LCR) | 27.7% | 80.3% | Qwen3.8 Max (0902) |
| DTBench | 57.9% | 92.0% | Qwen3.8 Max (0902) |
| LMCA | 12.0% | 46.2% | Qwen3.8 Max (0902) |
| Fiction.LiveBench | 36.0% | Not measured | Only Llama 4 Scout measured |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | 1279 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1248 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1249 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | 1118 | 1313 | Qwen3.8 Max (0902) |
| LMArena Text: English | 1304 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1252 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1255 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | 1273 | 1478 | Qwen3.8 Max (0902) |
| LMArena Text: Japanese | 1206 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Korean | 1207 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1283 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1278 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1263 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | 1265 | 1471 | Qwen3.8 Max (0902) |
| LMArena Text: multi-turn | 1280 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1265 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1269 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1242 | 1464 | Qwen3.8 Max (0902) |
| LMArena Vision: English | 1143 | 1311 | Qwen3.8 Max (0902) |
| LMArena Vision: Chinese | 1106 | 1358 | Qwen3.8 Max (0902) |
| LMArena Vision: reading text | 1117 | 1322 | Qwen3.8 Max (0902) |
| LMArena Vision: humor | 1102 | 1304 | Qwen3.8 Max (0902) |
| LMArena Vision: creative writing | 1126 | 1312 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 4 Scout | Qwen3.8 Max (0902) | 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 | Meta Llama 4 Scout | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | Meta Llama | Qwen |
| Weights | Open weights | No public weights listed |
| Released | April 5, 2025 | September 3, 2026 |
| Context window | 1.31M | 1M |
| Input $/Mtok | $0.175 | $2.00 |
| Output $/Mtok | $0.50 | $6.00 |
| Coding index | Not benchmarked | 62.4 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | $1.276 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 4 Scout better than Qwen3.8 Max (0902) for coding?
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding. Pick Llama 4 Scout for output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and a lower cost per solved task ($1.276 against $1.32).
Which is cheaper, Llama 4 Scout or Qwen3.8 Max (0902)?
Llama 4 Scout costs $0.175 per million input tokens and $0.50 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Llama 4 Scout costs $1.276 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, Llama 4 Scout or Qwen3.8 Max (0902)?
Llama 4 Scout, with 1.31M tokens against 1M.
How many benchmarks is the Llama 4 Scout vs Qwen3.8 Max (0902) comparison based on?
64 benchmarks have a result for both models as of October 22, 2026. Llama 4 Scout's coding index rests on 0 independent benchmarks and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.