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Technical articles, tutorials, and insights
Open Source Project #174: AirLLM — Run 70B Models on 4GB GPU, 405B on 8GB, and 2.8-Trillion-Parameter Kimi K3 on 3.7GB
AirLLM breaks the VRAM wall with layer-wise inference: splits transformer models into per-layer shards on disk, loads one layer at a time during inference, releases memory immediately after. No quantization, distillation, or pruning required. Runs 70B to 2.8T parameter models on consumer GPUs. Supports Llama 4, Qwen3, DeepSeek-V3/R1, Kimi K3. Optional 4bit/8bit block-wise compression for ~3x speedup. 25.8k Stars, Apache 2.0, pip install airllm.
Open Source Project of the Day (#161): Open Interpreter — Open-Source AI Coding Agent, Rewritten in Rust, Supporting Kimi, Qwen, and DeepSeek
Open Interpreter's Rust rewrite, built on the OpenAI Codex codebase, focused on getting the best agent performance out of low-cost open-weight models (Kimi K3, Qwen, DeepSeek). Built-in multi-harness system, Computer Use capabilities, ACP protocol support, and Codex SDK compatibility. 66k Stars, Apache-2.0.