Llama 4 Scout coding benchmark
Meta · API model Llama-4-Scout-17B-16E-Instruct · Results published 25 Oct 2026 · Benchmark v4
How Llama 4 Scout performed
Llama 4 Scout by Meta took the PomBench AI coding benchmark: every model gets the same prompt and writes self-contained browser code for a twelve-second scene: a Pomeranian runs across a backyard, jumps a puddle, enters its doghouse, retrieves a bone and turns toward the viewer. The video above is an independent offline browser recording of the code Llama 4 Scout returned, captured at 960 × 540 and 30 fps, with no organizer edits to the code.
In this Llama 4 Scout coding test the model produced 696 output tokens, including provider-reported reasoning (rank 46 of 46 by output tokens), and the known API cost was $0.0008 (rank 1 of 45, cheapest first). Is Llama 4 Scout good at coding? One task cannot answer that on its own, so this LLM coding benchmark lets you watch the result instead of reading a score: check the gait, the puddle jump and reflection, the doorway occlusion and whether the bone stays in the dog's mouth.
Then compare Llama 4 Scout vs Llama 4 Maverick and Muse Wonder below, or open the AI model comparison to play up to four models on one synchronized timeline.
Llama 4 Scout vs Llama 4 Maverick, Muse Wonder and GPT-4.1 Mini
- Llama 4 Scout vs Llama 4 Maverick: 696 vs 763 output tokens; known API cost $0.0008 vs $0.0013. Watch side by side
- Llama 4 Scout vs Muse Wonder: 696 vs 8,480 output tokens; known API cost $0.0008 vs $0.1778. Watch side by side
- Llama 4 Scout vs GPT-4.1 Mini: 696 vs 13,811 output tokens; known API cost $0.0008 vs $0.0229. Watch side by side
Llama 4 Scout code
Llama 4 Scout wrote its own native browser animation code from the same prompt as every other model. One execution repair is available for empty, truncated or unexecutable code; the final response is kept, not a best-of selection.