Model comparison
Seed 2.0 Pro vs Llama 4 Scout
Seed 2.0 Pro is the stronger model overall, scoring 43.2 to 27.7 on the Noometry Index. Llama 4 Scout costs 7.5× less per token, which makes it the better buy when Seed 2.0 Pro's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
ByteDance Seed
MetaSummary
- They share 18 benchmarks with published results for both. Seed 2.0 Pro scores higher in 9 categories and Llama 4 Scout in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Seed 2.0 Pro leads 62.9 to 37.0.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.50 / $3 for Seed 2.0 Pro.
- Seed 2.0 Pro accepts more context: 256K tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Seed 2.0 Pro | Llama 4 Scout | |
|---|---|---|
| Provider | ByteDance Seed | Meta |
| Noometry Index | 43.2 | 27.7 |
| Released | 2026-02-14 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 256K | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $0.50 | $0.10 |
| Output $ / M tokens | $3 | $0.30 |
| Results tracked | 20 | 43 |
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Category by category
Coding Seed 2.0 Pro leads
Seed 2.0 Pro: 43.5 (#86), Llama 4 Scout: 20.2 (#339)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1472 | 1286 |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Not comparable
Seed 2.0 Pro: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Seed 2.0 Pro leads
Seed 2.0 Pro: 24.1 (#165), Llama 4 Scout: 9.1 (#345)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1453 | 1266 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| NYT Connections (extended) | 28.4% | — |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| Thematic Generalization | 57.1% | — |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Epoch Capabilities Index | — | 129.64 |
| ForecastBench | — | 57.5 |
Math Seed 2.0 Pro leads
Seed 2.0 Pro: 39.3 (#108), Llama 4 Scout: 19.6 (#286)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Math | 1439 | 1287 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Seed 2.0 Pro leads
Seed 2.0 Pro: 40.2 (#122), Llama 4 Scout: 31.9 (#217)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Expert | 1440 | 1235 |
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
Multimodal Seed 2.0 Pro leads
Seed 2.0 Pro: 41.5 (#35), Llama 4 Scout: 32.2 (#102)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1274 | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Seed 2.0 Pro leads
Seed 2.0 Pro: 54.5 (#39), Llama 4 Scout: 41.0 (#212)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1441 | 1252 |
| LMArena Chinese | 1489 | 1255 |
| LMArena French | 1471 | 1282 |
| LMArena German | 1442 | 1272 |
| LMArena Japanese | 1408 | 1206 |
| LMArena Korean | 1411 | 1207 |
| LMArena Russian | 1449 | 1263 |
| LMArena Spanish | 1460 | 1278 |
Instruction Following Seed 2.0 Pro leads
Seed 2.0 Pro: 74.5 (#91), Llama 4 Scout: 65.8 (#217)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1414 | 1248 |
| IFEval | — | 81.8% |
Long Context Seed 2.0 Pro leads
Seed 2.0 Pro: 43.6 (#90), Llama 4 Scout: 27.5 (#294)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1428 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Seed 2.0 Pro leads
Seed 2.0 Pro: 62.9 (#69), Llama 4 Scout: 37.0 (#261)
| Benchmark | Seed 2.0 Pro | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1448 | 1279 |
| LMArena Creative Writing | 1406 | 1249 |
| LMArena Multi-Turn | 1441 | 1280 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
Frequently asked questions
Is Seed 2.0 Pro better than Llama 4 Scout?
Seed 2.0 Pro is the stronger model overall, scoring 43.2 to 27.7 on the Noometry Index. Llama 4 Scout costs 7.5× less per token, which makes it the better buy when Seed 2.0 Pro's lead doesn't matter for your workload.
Which is cheaper, Seed 2.0 Pro or Llama 4 Scout?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Seed 2.0 Pro lists at $0.50 and $3.
Is Seed 2.0 Pro or Llama 4 Scout better for coding?
Seed 2.0 Pro scores higher on coding benchmarks: 43.5 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Seed 2.0 Pro does, with 256K tokens against 128K.
How many benchmarks do Seed 2.0 Pro and Llama 4 Scout share?
18 benchmarks have published results for both models. Seed 2.0 Pro has 20 scored results on Noometry and Llama 4 Scout has 43.