Budget Pick
Apple M4 Ultra256 GB VRAM · ~3.8 tok/s
Lowest cost that meets recommended VRAM
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Can I Run Llama 4 Maverick 17B (128E)?
Llama 4 Maverick 17B (128E) is a 17B parameter model from the Llama family. Check if your hardware can handle it.
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1% of 1,613 scanned PCs run Llama 4 Maverick 17B (128E) fully on GPU.
335 keep at least some work on GPU. Based on anonymous compatibility checks.
Full GPU
21Hybrid CPU+GPU
314CPU Only
140Can't Run
1,138Test Your Hardware
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Hardware Requirements
Beginner tip: minimum values mean the model can start, while recommended values usually feel smoother during real use. VRAM is your GPU's dedicated memory; RAM is your system memory used as fallback. See the full glossary.
| Quantization | File Size | Min VRAM | Recommended VRAM | Min RAM | Context |
|---|---|---|---|---|---|
| Q4_K_MEasiest | 230 GB | 235 GB | 256 GB | 256 GB | 4K / 128K |
Not sure your GPU has enough VRAM? Compare GPUs that can run Llama 4 Maverick 17B (128E).
Recommended GPUs for Llama 4 Maverick 17B (128E)
These GPUs meet the recommended 256 GB VRAM for the Q4_K_M quantization. Estimated speeds are approximate and assume full GPU offloading.
Need a detailed comparison? See all GPU rankings for Llama 4 Maverick 17B (128E).
Strong OpenClaw Model Candidate
Llama 4 Maverick 17B (128E) is a common OpenClaw pick for local agent workflows. Use this model with Ollama, llama.cpp, or LM Studio, then confirm full OpenClaw hardware compatibility.
Why choose Llama 4 Maverick 17B (128E)?
General-purpose local model brief
- • Pilot testing with your own tasks
- • Controlled local experiments
Quantization tip: Benchmark at least two quantizations and validate with a task-specific eval set before production use.