@no_stp_on_snek: turboquant+ is now a swappable backend in LocalAI alongside tinygrad and sglang. if you're running GGUF models and want…
Summary
turboquant+ backend added to LocalAI, enabling longer context for GGUF models without hardware upgrade.
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@no_stp_on_snek: Very nice. Huge for team 3090. And TurboQuant+ is already implemented in a bunch of inference engines.
A reply celebrates Unsloth AI's upcoming Qwen3.8-27B model, which will run on 17GB RAM/VRAM setups, and notes TurboQuant+ is already integrated into many inference engines — great news for RTX 3090 users.
@no_stp_on_snek: got it here if ya want to try it out:
A fork of llama.cpp integrating TurboQuant+ for advanced KV-cache and weight quantization, with cross-backend kernel support (Apple Silicon, NVIDIA CUDA, AMD ROCm, Vulkan) and used in production by LocalAI, Chronara, and AtomicChat.
@coffeecup2020: TurboQuant - Qwopus3.6-27B-v2-TQ3_4S.gguf Confirmed with gpqa test this is something great. https://huggingface.co/YTan…
TurboQuant is a GGUF quantized version of the Qwopus3.6-27B-v2 model, confirmed with GPQA test results and shared on Hugging Face, with credits to Jackrong and KyleHessling.
Transformers now runs llama.cpp quants
Hugging Face's transformers library now supports GGUF models from llama.cpp, enabling efficient local inference on consumer hardware through familiar APIs.
@UnslothAI: GLM-5.2 can now be run locally! The 2-bit model retains ~82% accuracy after we shrunk it from 1.51TB to 238GB (-84% siz…
UnslothAI announces GLM-5.2, Z.ai's strongest open model with 744B parameters, now runnable locally via dynamic GGUF quantization reducing size by ~84% to 239GB while retaining ~82% accuracy. It fits on 256GB Macs and supports long-context, reasoning, and agentic tasks.