Deploy LLaMA 4
Text & ChatCatalogue notes · not a new performance benchmark
LLaMA 4 is Meta's latest open-weight model family. Scout uses a 109B MoE architecture with 17B active parameters, 10M token context window, and native multimodal capabilities. LLaMA 3.3 70B remains a strong general-purpose option.
Review a LLaMA 4 setup
Available Variants (2)
| Model | GPU | VRAM | Configured estimate | Action |
|---|---|---|---|---|
LLaMA 4 Scout Scout (109B MoE) | A100 80GB PCIe | 80 GB | Review current price | Deploy |
LLaMA 3.3 70B Large (70B) | RTX A6000 | 48 GB | Review current price | Deploy |
These configured estimates include the service fee and configured disk. Review the current quote before starting. Capacity, startup and output quality are not verified by this table.
Requirements
ModelPilot assigns 48–80GB cloud GPUs across the listed variants. Actual local VRAM requirements vary with model variant, precision, quantization, resolution, and workflow settings.
On ModelPilot, deploy on a dedicated cloud GPU (up to 80GB VRAM) with a current quote and spending controls shown before you start.
Use Cases
- ✓General-purpose AI assistants
- ✓Long-context document processing
- ✓Multimodal understanding
- ✓Enterprise AI applications
Related Models
Frequently Asked Questions
How much GPU memory is allocated for LLaMA 4?
The listed ModelPilot variants use 48–80GB cloud GPUs. Local memory needs vary with the variant, precision, quantization, and workflow settings.
How much does it cost to run LLaMA 4?
Pricing varies by hardware and storage. Review the current quote and spending controls before starting.
How long does LLaMA 4 take to deploy?
Startup depends on capacity, image and model downloads, and runtime readiness. The deployment page reports progress; a catalogue entry does not guarantee a startup time.
Can I run LLaMA 4 on my local GPU?
It depends on the selected variant, precision, quantization, and workflow settings. Compare the variants below with your available VRAM; the table shows ModelPilot's cloud GPU allocation, not a universal local minimum.
Ready to deploy LLaMA 4?
Pick a configuration, review its dependencies, licence, current quote and spending controls, then choose whether to start.