Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint

My comment on Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint — Hacker News.If you want to try out out the GGUFs from https://huggingface.co/prism-ml/Ternary-Bonsai-2-27B-gguf#th... be aware that you need Prism's llama.cpp fork to get them to work, from…

My comment on Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint — Hacker News.If you want to try out out the GGUFs from https://huggingface.co/prism-ml/Ternary-Bonsai-2-27B-gguf#th... be aware that you need Prism's llama.cpp fork to get them to work, from https://github.com/PrismML-Eng/llama.cpp/releases/tag/prism-... This should work: cd /tmp # Get the Prism macOS runtime curl -fL https://github.com/PrismML-Eng/llama.cpp/releases/download/prism-b10685-7dffb15/llama-prism-b10685-7dffb15-bin-macos-arm64.tar.gz -o bonsai-runtime.tar.gz tar -xzf bonsai-runtime.tar.gz # Get the ~5.95 GB GGUF model: curl -fL https://huggingface.co/prism-ml/Ternary-Bonsai-2-27B-gguf/resolve/main/Ternary-Bonsai-2-27B-PTQ1_0.gguf -o Ternary-Bonsai-2-27B-PTQ1_0.gguf # Run the server, I used port 8331 ./llama-prism-b10685-7dffb15/llama-server \ -m Ternary-Bonsai-2-27B-PTQ1_0.gguf \ --port 8331 -ngl 99 -fa on -c 32768 Then open http://localhost:8331 for the (very good) baked in llama-server web UI... or run a prompt via the API like this: uvx llm openai endpoint http://127.0.0.1:8331/v1 \ --model bonsai-2-27b --responses hi That's running at ~20 token/second for me on an M5 Pro (after a server restart I got 44 token/second, not sure why), but I'm pretty sure something isn't working right, on startup the server said "ggml_metal_device_init: - the tensor API is not supported in this environment - disabling". Tags: llama-cpp

Source: Simon Willison — Published September 17, 2026 at 22:13 UTC — Category: Tools