MDL
Llama 4 Scout
Meta
Verified against Artificial Analysis · Jul 13, 2026
Capability
43
percentile index
Price /M
$0.17 / $0.66
in / out
Context
10M
tokens
Avg score
33.3
11 benchmarks
AA Intelligence
10.0
index
Speed
107 tok/s
TTFT 0.6s
Released
Apr 5, 2025
About
Llama 4 Scout is a open-weights model in the Llama family from Meta. Benchmarked on 11 evals, averaging 33.3.
Benchmark scores · 11
avg 33.3 — higher is betterThe research behind this model
all papers mentioning it →FORGE: Self-Evolving Agent Memory With No Weight Updates via Population BroadcastMay 15, 2026Hybrid LLM-based Intelligent Framework for Robot Task SchedulingMay 15, 2026Retrieval-Augmented Large Language Models for Schema-Constrained Clinical Information ExtractionMay 14, 2026SPIN: Structural LLM Planning via Iterative Navigation for Industrial TasksMay 13, 2026Three Regimes of Context-Parametric Conflict: A Predictive Framework and Empirical ValidationMay 12, 2026
Mentions matched by name in title/abstract — from the arXiv + HF daily corpus.
Performance & price
Output speed107 tok/s
Latency (TTFT)0.6s
Price in / out$0.17 / $0.66 per 1M
Blended price$0.292 / 1M
Coding index8.2
Math index14.0
Median across API providers, via Artificial Analysis. Blended = 3:1 input:output. For reasoning models, latency includes thinking time. Methodology →
History
full ledger →Capability over time
Append-only ledger — every observed change to this model's numbers.
API providers
Artificial Analysis$0.66/M