YOUR MEMORY BUDGET

Local AI models for 12GB VRAM.

Explore models by theoretical weight storage. This shortlist covers available downloadable language models with a known or name-derived parameter count.

10 GBleft for weights at 4-bit
12 GB budget − 2 GB reserve

The reserve is your assumption, not a measured overhead allowance. The default 2 GB may be too little for your runtime or context length. Results are not confirmed fits and have no verified speed rating. Weight estimates use decimal GB and do not include quantization overhead.

328 models within the weight budget

Largest parameter count first · not a quality ranking

Z.ai · Downloadable

glm-4-9b-hf

Text generation

Generates text for conversations and writing.

Source listed
Jan 16, 2025
Parameters
9B
4-bit weights only
≈ 4.5 GB
License
other
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Z.ai · Downloadable

GLM-4.1V-9B-Thinking

VisionReasoning

Understands text and images and responds in text. Supports a reasoning mode.

Source listed
Jun 28, 2025
Parameters
9B
4-bit weights only
≈ 4.5 GB
License
mit
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Meta · Downloadable

Llama-3.1-8B

Text generation

Generates text for conversations and writing.

Source listed
Jul 14, 2024
Parameters
8B
4-bit weights only
≈ 4 GB
License
llama3.1
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Microsoft · Downloadable

UserLM-8b

Text generation

Generates text for conversations and writing.

Source listed
Sep 30, 2025
Parameters
8B
4-bit weights only
≈ 4 GB
License
mit
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NVIDIA · Downloadable

4D-RGPT-8B

Video understanding

Generates text for conversations and writing.

Source listed
Jun 2, 2026
Parameters
8B
4-bit weights only
≈ 4 GB
License
cc-by-nc-4.0
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NVIDIA · Downloadable

EGM-8B-SFT

Vision

Understands text and images and responds in text.

Source listed
Apr 2, 2026
Parameters
8B
4-bit weights only
≈ 4 GB
License
apache-2.0
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What changes with a 12GB budget?

With 2 GB set aside, 10 GB remains for weights. At 4-bit that allows up to 20 billion parameters in the theoretical calculation. An 8-billion-parameter model alone needs approximately 4 GB at this precision, before its conversation cache and runtime.

Why might a listed model still fail to load?

Its actual weight format may need more space, the runtime may not support its architecture, or the conversation cache may exceed your reserve. Vision models can also need space for image processing. Check the original model card and measure your exact setup before relying on it.

Read the memory guide and technical sources · Compare two models