YOUR MEMORY BUDGET

Local AI models for 24GB VRAM.

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

22 GBleft for weights at 4-bit
24 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.

405 models within the weight budget

Largest parameter count first · not a quality ranking

Z.ai · Downloadable

SWE-Dev-32B

Text generation

Generates text for conversations and writing.

Source listed
Apr 6, 2025
Parameters
32B
4-bit weights only
≈ 16 GB
License
mit
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Google · Downloadable

gemma-4-31B

Vision

Understands text and images and responds in text.

Source listed
Mar 12, 2026
Parameters
31B
4-bit weights only
≈ 15.5 GB
License
apache-2.0
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Google · Downloadable

gemma-4-31B-it

Vision

Understands text and images and responds in text.

Source listed
Mar 11, 2026
Parameters
31B
4-bit weights only
≈ 15.5 GB
License
apache-2.0
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NVIDIA · Downloadable

Gemma-4-31B-IT

Text generation

Generates text for conversations and writing.

Source listed
Apr 2, 2026
Parameters
31B
4-bit weights only
≈ 15.5 GB
License
other
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Qwen · Alibaba · Downloadable

Qwen3-30B-A3B

Text generation

Generates text for conversations and writing.

Source listed
Jun 11, 2025
Parameters
30B
4-bit weights only
≈ 15 GB
License
apache-2.0
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What changes with a 24GB budget?

With 2 GB set aside, 22 GB remains for weights. At 4-bit that allows up to 44 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