Llama 4 Scout
Meta released 2025-04-05 llama-4-community
DeepSeek V4 Flash 0731 scores higher and costs less — but you would give something up.
+41.5 on the capability index and 30% cheaper ($0.105/M against $0.150/M). What you lose:
- no image input
Capability scores do not measure context length, output ceiling or which inputs a model accepts, so a higher score does not mean a drop-in replacement.
Every price dimension
| Input | $0.100/M |
|---|---|
| Output | $0.300/M |
Independent scores
| Intelligence | 10.3 |
|---|---|
| Coding | 8.2 |
| Agentic | 1.1 |
Sources are listed separately rather than averaged. Across the 62 models both have scored they correlate at r = 0.806 — close agreement overall, but four models rank very differently between them, and a blended score would hide exactly those.
Capability
| Context window | 1.3M |
|---|---|
| Max output | 16K |
| Input modes | text, image |
| Tool use | yes |
| Reasoning | no |
| Knowledge cutoff | 2024-08-31 |
| Open weights | yes |
Provenance
| Price source | openrouter.ai |
|---|---|
| Fetched | 2026-08-24 |
| Quality data | verified |
| Cross-checked | vendor page |
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...