What is GLM-5.2: China’s AI model challenging Anthropic’s Claude Fable 5 in coding and long-context reasoning

In recent days, a new large language model from China has started circulating through technical circles with an unusual mix ...

DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85%

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.
Developer Tech

What is GLM-5.2? Z.ai targets coding agents

Z.ai’s GLM-5.2 is an open-source model aimed at long-context coding-agent workflows, with support for a one million-token ...
Developer Tech

NVIDIA: DFlash block diffusion accelerates autoregressive LLMs

Deploying DFlash block diffusion on NVIDIA hardware accelerates autoregressive LLMs during latency-sensitive inference.
Tech Times

NVIDIA Diffusion LLM Hits 2.42x Throughput Without Retraining: Nemotron TwoTower Released

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...
Tech Times

DeepSeek Releases DSpark: Speculative Decoding Makes V4 Up to 85 Percent Faster

DeepSeek speculative decoding framework DSpark went live June 27 on V4-Flash and V4-Pro, reporting up to 85 percent faster ...

Z.ai’s open-weights GLM-5.2 beats GPT-5.5 on multiple long-horizon coding benchmarks for 1/6th the cost

It allows engineering teams to host frontier-level AI on their own sovereign infrastructure, entirely eliminating vendor lock ...
Computerworld

Z.ai pitches GLM-5.2 for long-running software engineering tasks

The open-source model combines a one-million-token context window with architectural updates aimed at lowering the cost of repository-scale AI coding. Z.ai has released GLM-5.2, an MIT-licensed ...

Waterloo's PAW compiles task specs into 23MB LoRA adapters a 600M-parameter model runs entirely offline.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2, 2026, a system that compiles any natural-language task spec into a 23MB ...