Meta AIopen-weight
Released: 2025-04-05

Llama 4 Scout

Meta ultra-long-context open-weight workhorse model featuring an unprecedented 10M token context window.

Intelligence Index
89.2/ 100
Calibrated multi-domain composite
Throughput Speed
140tok/sec
Output streaming throughput
Time To First Token
310ms
Initial chunk server latency
LiveBench Contam-Free
76.0%
September 2026 suite score

LiveBench Multi-Domain Evaluation Breakdown

Monthly refreshed contamination-free test sets
Logical Reasoning87.0%
Coding & Repo Repair77.5%
Mathematics (AIME)87.0%
Data Analysis & Tables80.0%
Language & Comprehension84.0%
Instruction Following89.0%

Sourced Benchmark Evaluations (3)

Verified performance across authoritative benchmarks with provenance tracking.
BenchmarkStatusScoreTrustDateSource TypeProvenance
ARC-AGI-2Nearing Saturation69%
75
2025-05-03independentSource ↗
SWE-bench VerifiedSaturated58.9%
25
2025-04-14independentSource ↗
IFEvalDeprecated89%
25
2025-04-09independentSource ↗
Local Hardware Execution (Ollama)Hardware Compatible
# 1. Pull and execute model locally with Ollama
ollama run llama-4-scout

# 2. Or invoke via local OpenAI-compatible endpoint
curl http://localhost:11434/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-4-scout",
    "messages": [{"role": "user", "content": "Analyze reasoning chains on AIME 2026"}]
  }'

Evaluation & Sourcing Notes

Scores listed for Llama 4 Scout represent verified evaluations extracted from official research papers, independent evaluation suites (HELM, LMSYS, OpenCompass, LiveBench), and verified audit reports.

All benchmarks marked as saturated or deprecated reflect historical performance where the benchmark no longer provides active discriminative power.