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text model · Llama 4 · Windows

Can I run Llama 4 Maverick on Nvidia GeForce RTX 4060 Ti (16GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Llama 4 Maverick needs ~231.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.

Needs ~231.7 GB Device usable ~15 GB

Needs ~231.7 GB even at Q4_K_M, but only ~15 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 216.7 GB: Llama 4 Maverick needs roughly 231.7 GB at Q4_K_M and Nvidia GeForce RTX 4060 Ti (16GB) leaves only about 15 GB usable for a model. No single tracked device has enough memory; Llama 4 Maverick needs a multi-GPU or high-memory rig.

Q4_K_M needed
~231.7 GB
Usable on device
~15 GB
Device memory
16 GB
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Which quant fits

Quant ladder vs ~15 GB usable
Q2_K
~173.1 GB
Q3_K_M
~201.1 GB
Q4_K_M
~231.7 GB
Q5_K_M
~290.6 GB
Q6_K
~333.6 GB
Q8_0
~402.2 GB
FP16
~806.6 GB
The line marks Nvidia GeForce RTX 4060 Ti (16GB)'s ~15 GB budget; rungs past it are too large.
Model Llama 4
Parameters
400B (MoE, 17B active)
Q4_K_M size
226.09 GB
Q8_0 size
396.57 GB
Context
1000k
Ollama tag
llama4:128x17b
Full Llama 4 Maverick requirements →
Device Windows
Memory
16 GB vram
Usable for weights
~15 GB
Power draw
~165 W
Best runtime
Ollama (CUDA) / llama.cpp CUDA
Best models for Nvidia GeForce RTX 4060 Ti (16GB) →

What you can run instead

FAQ

Can Nvidia GeForce RTX 4060 Ti (16GB) run Llama 4 Maverick?

No. Llama 4 Maverick needs ~231.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.

How much memory does Llama 4 Maverick need?

Nvidia GeForce RTX 4060 Ti (16GB) does not have enough memory. At Q4_K_M the weights are ~226.09 GB; with KV cache and runtime overhead, budget ~231.7 GB at a 4k context. It is a Mixture-of-Experts model (400B total / 17B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Llama 4 Maverick on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.