DeepSeek V3 0324 vs Llama 4 Scout
DeepSeek V3 0324 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 9.7 to 6.5, and Llama 4 Scout costs 2.1x less per output token ($0.50 vs $1.07 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
DeepSeek V3 0324 or Llama 4 Scout: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 31
- DeepSeek V3 0324 only
- 5
- Llama 4 Scout only
- 51
- 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
DeepSeek V3 0324
DeepSeek V3 0324 leads, 9.7 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V3 0324
DeepSeek V3 0324 leads, 0.8 against 0.5.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V3 0324
DeepSeek V3 0324 leads, 61.6% against 47.0%.
Same board, both measured
Math
AIME
DeepSeek V3 0324
DeepSeek V3 0324 leads, 52.2% against 19.0%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V3 0324
DeepSeek V3 0324 leads, 79.5% against 69.6%.
Same board, both measured
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 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Scout
DeepSeek V3 0324 $0.0008, 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
- DeepSeek V3 0324 not benchmarked, Llama 4 Scout not benchmarked.
- Widest category
- Math, 20.5 points apart on average over 7 shared benchmarks.
- Widest single gap
- AIME: DeepSeek V3 0324 52.2% against Llama 4 Scout 19.0%, 33.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Llama 4 Scout $0.50 per million output tokens, 2.1x apart.
- Context window
- DeepSeek V3 0324 takes 164K 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 | DeepSeek V3 0324 | Bars | Llama 4 Scout | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 7 | 0 | ||
| Knowledge | 6 | 0 | ||
| General | 5 | 0 | ||
| All shared boards | 31 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | 9.1% | DeepSeek V3 0324 |
| AA Coding Index | 21.2 | 8.2 | DeepSeek V3 0324 |
| LiveCodeBench (Vals AI) | 65.5% | 38.5% | DeepSeek V3 0324 |
| LiveCodeBench (Artificial Analysis run) | 40.5% | 29.9% | DeepSeek V3 0324 |
| SciCode | 39.0% | 21.3% | DeepSeek V3 0324 |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 1.5% | DeepSeek V3 0324 |
| WeirdML | 36.1% | Not measured | Only DeepSeek V3 0324 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 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 6.5 | DeepSeek V3 0324 |
| Epoch Capabilities Index | Not measured | 129.6 | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 0.5 | DeepSeek V3 0324 |
| τ²-Bench Telecom | 47.1% | 15.5% | DeepSeek V3 0324 |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| 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 index40
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 47.0% | DeepSeek V3 0324 |
| MMMU Pro (Vals AI) | Not measured | 58.8% | Only Llama 4 Scout measured |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 58.7% | DeepSeek V3 0324 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 3.8% | DeepSeek V3 0324 |
| GPQA Diamond (Epoch AI run) | 67.6% | 51.8% | DeepSeek V3 0324 |
| ARC-AGI | Not measured | 0.5% | Only Llama 4 Scout measured |
| ARC-AGI-2 | Not measured | 0.0% | Only Llama 4 Scout measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 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 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| AIME | 52.2% | 19.0% | DeepSeek V3 0324 |
| MATH 500 (Vals AI) | 88.6% | 79.2% | DeepSeek V3 0324 |
| MGSM (Vals AI) | 91.7% | 88.0% | DeepSeek V3 0324 |
| AA Math Index | 41.0 | 14.0 | DeepSeek V3 0324 |
| AIME 2025 (Artificial Analysis run) | 41.0% | 14.0% | DeepSeek V3 0324 |
| OTIS Mock AIME | 37.8% | 7.8% | DeepSeek V3 0324 |
| MATH level 5 | 75.5% | 62.3% | DeepSeek V3 0324 |
| LMArena Text: math | Not measured | 1287 | Only Llama 4 Scout measured |
| LMArena Text: mathematical work | Not measured | 1286 | Only Llama 4 Scout measured |
| MathArena | 7.1% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V3 0324 | Llama 4 Scout | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 69.6% | DeepSeek V3 0324 |
| LegalBench (Vals AI) | 77.7% | 72.0% | DeepSeek V3 0324 |
| CorpFin (Vals AI) | 54.7% | 46.8% | DeepSeek V3 0324 |
| TaxEval (Vals AI) | 71.1% | 55.2% | DeepSeek V3 0324 |
| MortgageTax (Vals AI) | Not measured | 57.8% | Only Llama 4 Scout measured |
| MedQA (Vals AI) | 82.0% | 50.9% | DeepSeek V3 0324 |
| MedCode (Vals AI) | Not measured | 23.3% | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | 75.2% | DeepSeek V3 0324 |
| 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 | DeepSeek V3 0324 | 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 index50
| Benchmark | DeepSeek V3 0324 | 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 | 41.0% | 39.5% | DeepSeek V3 0324 |
| Long context reasoning (AA-LCR) | 40.7% | 27.7% | DeepSeek V3 0324 |
| DTBench | 64.8% | 57.9% | DeepSeek V3 0324 |
| LMCA | 15.5% | 12.0% | DeepSeek V3 0324 |
| Fiction.LiveBench | 50.0% | 36.0% | DeepSeek V3 0324 |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 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 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | 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 | DeepSeek V3 0324 | Meta Llama 4 Scout |
|---|---|---|
| Maker | DeepSeek | Meta Llama |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | April 5, 2025 |
| Context window | 164K | 1.31M |
| Input $/Mtok | $0.27 | $0.175 |
| Output $/Mtok | $1.07 | $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 DeepSeek V3 0324 better than Llama 4 Scout for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, DeepSeek V3 0324 or Llama 4 Scout?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 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, DeepSeek V3 0324 or Llama 4 Scout?
Llama 4 Scout, with 1.31M tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs Llama 4 Scout comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324'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.