ExLlama vs ExLlamaV2

A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.

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EX ExLlama Memory-efficient inference library for quantized Llama models VS EX ExLlamaV2 Fast inference library for quantized LLMs on consumer GPUs

Feature	ExLlama	ExLlamaV2
Deploy effort	Read-the-docs project	Read-the-docs project
Health score	23 · At risk	62 · Good
Category	Self-Hosted AI	Self-Hosted AI
License	MIT	MIT
Language	Python	Python
Setup difficulty	Hard	Hard
Min. RAM	8,192 MB	8,192 MB
Deployment	source	bare-metal, source
GitHub stars	★ 2,946	★ 4,627
First released	2023	2023
Replaces	OpenAI API	OpenAI API

What are ExLlama and ExLlamaV2?

ExLlama

ExLlama is a standalone Python/C++/CUDA implementation for running quantized GPTQ Llama models with low VRAM use on modern GPUs. It is the predecessor to ExLlamaV2 and focuses on fast, memory-efficient local inference.

Low VRAM GPTQ inference
CUDA-accelerated
Standalone library
Fast token generation

ExLlamaV2

ExLlamaV2 is an inference library optimized for running quantized large language models efficiently on modern consumer GPUs. Its EXL2 quantization format allows flexible bitrates for the best speed-quality balance.

EXL2 flexible quantization
Fast single-GPU inference
Low memory footprint
Built-in server