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The latest AI and developer news about #quantization, with the original source and a short summary.

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#quantization - page 3 | AI Briefing

PickPOCKET-Image: Solving On-Device Korean Text Rendering

·2·2026.07.26 17:00

SLQ, a Statistically Lossless Quantization Technique for LLMs, Unveiled

·2026.07.25 03:00

audio.cpp 0.4, Supports 35 TTS Model Families

·2026.07.24 09:00

Diffusers Officially Supports Nunchaku 4-bit Quantization

·2026.07.23 09:00

BTL-3 27B Agentic Model Released

·2026.07.23 04:00

llama.cpp Improves AMD ROCm Performance and Fixes Bugs

·2026.07.21 15:00

Qwen2.5-Coder Quantization Performance Study Results

·2026.07.20 16:00

BeeLlama.cpp v0.4.0 Released

·2026.07.20 03:00

Study on the Mismatch Between Reconstruction Error and Downstream Performance

·2026.07.20 00:00

llama.cpp Improves Inference Performance for Bonsai Model

·2026.07.16 13:00

Bonsai 27B: On-Device Execution via 1-bit/Ternary Quantization

·2026.07.16 12:00

colibri: Running a 744B MoE on a Consumer PC

·2026.07.14 15:00

Unsloth Releases NVFP4 Quantization for Qwen3.6

·1·2026.07.13 19:00

ggml Adds Q2_0 Quantization to Support Ternary Bonsai

·2026.07.08 23:00

Sana 1.6B Model Released with 1.58-bit Quantization

·2026.06.28 14:00

EdgeRazor: A Lightweight LLM Framework Supporting 1.58-bit Quantization

·2026.06.25 01:00

OSCAR: 2-bit KV Cache Quantization Technique Released

·2026.06.10 04:00

Three builders' case studies using Gemma 4

·1·2026.06.10 01:00

llama.cpp WebGPU Inference Performance Improved

·2026.06.09 11:00

NanoQuant: Implementing Sub-1-Bit Quantization

·2026.06.09 01:00

Gemma 4 QAT MTP Heads Released and Bug Fixed

·1·2026.06.07 06:00

Launch HN: General Instinct (YC P26) – Frontier models for edge devices

·2026.06.06 01:00

PickGemma 4 QAT Models: Optimizing Model Compression for Mobile and Laptop Efficiency

·2026.06.06 01:00

Unsloth releases Gemma 4 GGUF weights

·2026.06.06 00:00

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