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ModelTape / Models / Llama 4 Scout
Meta · open-weights

Llama 4 Scout

Llama 4 Scout is an open-weights language model from Meta, released April 5, 2025. On the Epoch Capabilities Index it scores 127.7, rank 163 of 256 rated models.

Check it against your own PC →

Lab
Meta
Released
April 5, 2025
Weights
Open restricted use
Parameters
–
Context
–
Price / M tokens
–
Epoch ECI
127.7 #163

Can you run Llama 4 Scout locally?

Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMSize unknown––––
8 GB VRAMSize unknown––––
12 GB VRAMSize unknown––––
16 GB VRAMSize unknown––––
24 GB VRAMSize unknown––––
32 GB VRAMSize unknown––––

Parameter count unknown. The weights may not be on Hugging Face yet.

Strengths by category

ModelTape's 0–100 fit on Epoch AI benchmark results.

CategoryScoreBased on
Math14.5MATH level 5, OTIS Mock AIME 2024-2025, FrontierMath-2025-02-28-Private

Benchmark results

Benchmark (Epoch AI)Score
MATH level 562.3%
GPQA Diamond37.3%
OTIS Mock AIME7.7%
FrontierMath-2025-02-28-Private0.0%

Links

Epoch AI benchmarks

Models with a similar score

Qwen2.5-Max · Gemini 1.5 Pro (Sept 2024) · Claude 3.5 Sonnet · Grok-2 (Dec 2024) · Phi-4 · GPT-4o (Nov 2024) · GPT-4o (May 2024) · Llama 3.1-405B

More from Meta

Muse Ember · Muse Spark Open · Muse Wonder · Muse Wonder Full · Muse Spark 1.3 · Muse Spark 1.3 Contributor · Muse Glimmer · Muse Glimmer 30B assistant

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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