Llama 4.5 — local AI model by Meta
Written by Jakub Rusinowski · Last updated
Llama 4.5, reported as a June 2026 mid-cycle refresh of Llama 4 Scout and Maverick. UNVERIFIED: secondary sources disagree on whether this release happened, and no primary source has been read. Meta's confirmed 2026 open release is Muse Glimmer 30B (10 August, Apache-2.0).
Variants
The smallest Llama 4.5 variant needs about 67 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache.
| Model | VRAM at Q4 | VRAM | Context | Run it |
|---|---|---|---|---|
| Llama 4.5 Scout → 109B (17B active) | ~66.6 GB | 10,000,000 | ollama run llama-4-5 |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Llama 4.5 locally
Install Ollama, then pull the tag.
ollama run llama-4-5Pick a size above for its own VRAM figure, speed estimate and install command.
Licence
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Applies to: Llama 4.5 ScoutRecommended GPU
The cheapest catalogued GPU that runs Llama 4.5 locally (min 67 GB VRAM) is the NVIDIA DGX Spark (128 GB).
Can I run Llama 4.5 on my GPU?
- Llama 4.5 on AMD Ryzen AI Max+ 395
- Llama 4.5 on Apple M1 Max
- Llama 4.5 on Apple M1 Pro
- Llama 4.5 on Apple M1 Ultra
- Llama 4.5 on Apple M2 Max
- Llama 4.5 on Apple M2 Pro
- Llama 4.5 on Apple M3 Max
- Llama 4.5 on Apple M3 Pro
- Llama 4.5 on Apple M4
- Llama 4.5 on Apple M4 Max
- Llama 4.5 on Apple M5
- Llama 4.5 on Apple M5 Max
- Llama 4.5 on Apple M5 Pro
- Llama 4.5 on NVIDIA A100 80GB (PCIe)
- Llama 4.5 on NVIDIA DGX Spark
- Llama 4.5 on NVIDIA GeForce RTX 5090
- Llama 4.5 on NVIDIA H100 80GB (PCIe)
- Llama 4.5 on NVIDIA L40S
- Llama 4.5 on NVIDIA RTX 6000 Ada Generation
- Llama 4.5 on NVIDIA RTX PRO 6000 Blackwell
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?
Llama 4.5 has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.