Llama 4.5 — Local AI Model by Meta

作者： Jakub Rusinowski · 最后更新： 2026年7月10日

PREVIEW (June 2026, specs unverified). Meta's iteration on Llama 4 — a Scout-class MoE (~109B total / ~17B active) with a very long context window, under the Llama Community license (700M MAU cap). Numbers carried from the Llama 4 Scout lineage; verify against the Hugging Face model card.

Hardware Requirements

Llama 4.5 ScoutMin 67 GB VRAM · Q4_K_M · 10,000,000 ctx ·

Recommended GPU

The cheapest GPU that runs Llama 4.5 locally (min 67 GB VRAM) is the AMD Ryzen AI Max+ 395 (96 GB).

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GMKtec EVO-X2 (Ryzen AI Max+ 395, 128GB)
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How to Run Locally

Install Ollama then run: ollama run

Minimum VRAM: 67 GB. For best results use Q4_K_M quantization.

Llama 4.5 — Frequently Asked Questions

How much VRAM does Llama 4.5 need?

Llama 4.5 needs about 67 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Llama 4.5 Scout (67 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Llama 4.5 on an RTX 4090 (24 GB)?

Llama 4.5's smallest variant needs about 67 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.

What quantization should I use for Llama 4.5?

Q4_K_M is the best balance of quality and VRAM for Llama 4.5 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Llama 4.5 with Ollama?

Install Ollama, then run: ollama run . This downloads Llama 4.5 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.

Can I Run Llama 4.5 on My GPU?