Open-weight local LLM

Llama 4 Maverick (17B/128E MoE)

Meta's largest open MoE. 17B active params across 128 experts (~400B total). Multimodal with exceptional image reasoning. Server-grade hardware required. Llama 4 License.

Server-grade 320 GB RAM Q4_K_M Maximum quality outputs
Parameters
17B active (400B total, 128 experts)
Minimum RAM
320 GB
Model size
220 GB
Quantization
Q4_K_M

Can Llama 4 Maverick (17B/128E MoE) run locally?

Llama 4 Maverick (17B/128E MoE) is server-grade locally. Keep it for comparison unless you have very large unified memory, multiple GPUs or remote inference.

Search for llama-4-maverick in LM Studio or another GGUF-compatible runtime.

chatvisionquality

Install path

01
Check RAM fitMinimum 320 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch llama-4-maverick in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Largest open MoE model from Meta
  • Incredible multimodal capabilities
  • Top-tier on all benchmarks

Limitations

  • Requires 320GB+ RAM
  • Server-grade hardware only
  • Very slow on consumer hardware

Best use cases

  • Maximum quality outputs
  • Research
  • Enterprise multimodal AI
  • Frontier tasks

Capability profile

speed
1
quality
10
coding
10
reasoning
10

Technical notes

Developer
Meta AI
License
Llama 4 Community License
Context window
131,072 tokens
Architecture
Mixture of Experts (MoE) — 400B total with native vision

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

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Where to go next