A 2-bit quantized GGUF of GLM-5.3 has been released for local inference, shrinking the model from 1.51TB to 239GB while retaining roughly 81% accuracy. It runs on 256GB Macs or equivalent RAM/VRAM setups. The release makes the strongest open model to date, per the poster, accessible to local users.
A senior software engineer tested Xiaomi's MiMo-V2.6-Pro and MiMo-V2.6-Flash after their strong benchmark scores and found serious real-world shortcomings. Pro failed a security sandboxing task with nine bypass holes found by GLM-5.3, while Flash spiraled destructively on a simple git task. The reviewer concludes the models underperform peers like GLM-5.3 and Qwen3.8 despite topping open-source leaderboards.
A senior software engineer tested Xiaomi's MiMo-V2.6-Pro and MiMo-V2.6-Flash after their strong benchmark scores and found serious real-world shortcomings. Pro failed a security sandboxing task with nine bypass holes found by GLM-5.3, while Flash spiraled destructively on a simple git task. The reviewer concludes the models underperform peers like GLM-5.3 and Qwen3.8 despite topping open-source leaderboards.
The open-source WARP engine (formerly WASTE), originally built to run the 2.78-trillion-parameter Kimi K3 on macOS, now supports GLM-5.3-Flash. It requires as little as 5.14 GB of RAM, enabling the 313B-parameter model to run on a MacBook with 8GB RAM. On a 64GB MacBook Pro M5 Pro, it achieves about 3.32 tokens per second, or 3.86 on longer runs.
The open-source WARP engine (formerly WASTE), originally built to run the 2.78-trillion-parameter Kimi K3 on macOS, now supports GLM-5.3-Flash. It requires as little as 5.14 GB of RAM, enabling the 313B-parameter model to run on a MacBook with 8GB RAM. On a 64GB MacBook Pro M5 Pro, it achieves about 3.32 tokens per second, or 3.86 on longer runs.
Mistral AI announced that GLM-5.3 is now available in Vibe Code for Pro, Team and Enterprise users, hosted and served by Mistral in the EU. The model is offered with up to 1M tokens of context and generous usage limits. A Mistral PM invited developer feedback in the announcement thread.
Mistral AI announced that GLM-5.3 is now available in Vibe Code for Pro, Team and Enterprise users, hosted and served by Mistral in the EU. The model is offered with up to 1M tokens of context and generous usage limits. A Mistral PM invited developer feedback in the announcement thread.
A user tested GLM 5.2 on a standard computer and was impressed by its capabilities and security, finding them similar to Claude or GPT. They began converting the model to int4 and exploring MTP usage to avoid out-of-memory errors.
A user tested GLM 5.2 on a standard computer and was impressed by its capabilities and security, finding them similar to Claude or GPT. They began converting the model to int4 and exploring MTP usage to avoid out-of-memory errors.
A developer released Quantprobe, an open-source memory allocation optimization framework that lets users run large local LLMs on old hardware. It achieves 30B parameter models at 22 tokens per second on a 6GB GPU with 16GB RAM. The tool aims to maximize performance for specific use cases.
A developer released Quantprobe, an open-source memory allocation optimization framework that lets users run large local LLMs on old hardware. It achieves 30B parameter models at 22 tokens per second on a 6GB GPU with 16GB RAM. The tool aims to maximize performance for specific use cases.