AirLLM Files

AirLLM v3.0.0

Big update: AirLLM now runs today's largest open models on tiny GPUs, with full support for the latest model families and Hugging Face versions — still no quantization, distillation, or pruning required.

Highlights

• Run the biggest open models on a single small GPU. Stream 70B models on 4GB, 405B Llama 3.1 on 8GB, and even DeepSeek-V3 (671B) on ~12GB.
• Native FP8 support. Pre-quantized FP8 (block-FP8) checkpoints now load and run correctly — including DeepSeek-V3 and the Qwen3-FP8 family.
• Latest models supported, including Qwen3 (dense + MoE, e.g. Qwen3-32B, Qwen3-30B-A3B, Qwen3-235B-A22B-FP8), DeepSeek-V3, Phi-4, Mixtral-8x7B, and DeepSeek-V2-Lite.
• Up to date with modern Hugging Face. Works with current transformers / accelerate releases, so a plain pip install airllm just works — no manual dependency juggling.

Improvements & fixes

• Reworked layer streaming to build on the standard Transformers model path for better model compatibility and generate() behavior.
• Runtime precision now follows each model's native dtype (e.g. bfloat16) instead of being forced to fp16, fixing garbled output on very deep models.
• Fixed weight loading for layers whose tensors span multiple checkpoint shards (affected large FP8/MoE models).
• More robust shard naming and attention-implementation fallback.

Install / upgrade

:::bash
pip install --upgrade airllm

See the README for quickstart and the full list of supported models.