AI is happening. The future is updating.Tess-4.5-27B-GGUF
Tess-4.5 is a 27-billion-parameter open-weights model for real engineering work. It reasons through every step, works with the tools and files actually in front of it, and runs on a single GPU or a laptop. On BenchLocal it matches its base, Qwen3.8-27B, with 25% fewer tokens. This repository holds the GGUF quantizations for llama.cpp, the vision projector and the multi-token-prediction draft heads. MTP speculative decoding needs a recent upstream llama.cpp build. On a 24 GB GPU at very long contexts, quantize the KV caches (`--cache-type-k q4_0 --cache-type-v q4_0`, and `-ctkd q4_0 -ctvd q4_0` for the draft) or lower `-c`. Tess works best when it knows where it is. State the working directory in the system prompt and attach your real tool definitions:
Tess-4.5 is a 27-billion-parameter open-weights model for real engineering work. It reasons through every step, works with the tools and files actually in front of it, and runs on a single GPU or a laptop. On BenchLocal it matches its base, Qwen3.8-27B, with 25% fewer tokens. This repository holds the GGUF quantizations for llama.cpp, the vision projector and the multi-token-prediction draft heads. MTP speculative decoding needs a recent upstream llama.cpp build. On a 24 GB GPU at very long contexts, quantize the KV caches (`--cache-type-k q4_0 --cache-type-v q4_0`, and `-ctkd q4_0 -ctvd q4_0` for the draft) or lower `-c`. Tess works best when it knows where it is. State the working directory in the system prompt and attach your real tool definitions: