glm

Luke Alonso uploaded an NVFP4 quantized version of GLM 5.2 (467GB) that can fit on 4x DGX Sparks hardware, costing approximately $20k.

GLM 5.2 appears to be a strong model update, but its launch is controversially conflating two different benchmark metric sets.

A user claims that the open-source GLM 5.2 model outperforms Opus 4.8 in Claude Code for coding tasks, expressing disbelief.

GLM-5.2 adopts MTP (Multi-Token Prediction) technology to accelerate inference and fixes a training-inference discrepancy in GLM-5.1's MTP that caused KV cache mixing issues.

Compares the improvements from GLM 5.1 to 5.2 and Qwen 3.5 to 3.6, discussing which update is more impressive.

A new agentic benchmark has been released, with Claude Fable and GLM 5.2 topping their respective cohorts.

A user reports running GLM 5.2 locally on a Mac Studio with 2-bit quantization, claiming it outperforms Opus 4.8 and enables free, private superintelligence for coding and agent tasks.

The founder of Z.ai expresses confidence in releasing a fable-class GLM model before the end of the year.

GLM founder hints at release of GLM-fable model before end of year.

Zhipu AI released GLM 5.2, a new version of their large language model, as demonstrated in a video created using the model itself.

IndexShare is a technique in the GLM-5.2 report that shares a single indexer across multiple layers in sparse attention, reducing FLOPs by 2.9x at 1M context by avoiding redundant top-key selections per layer.

unsloth has uploaded a GGUF version of GLM-5.2 to Hugging Face, providing ready-to-use model files for various inference engines like llama.cpp, vLLM, and SGLang.

GLM 5.2 is a powerful new AI model release, likely from Zhipu AI, described as a beast in performance.

A user asks about the feasibility of running GLM-5.2 at 4-bit quantization on four Ascend GX10s or DGX Sparks, wondering about speed and memory for 100k context.

A discussion on the cheapest local hardware setups for running GLM 5.x and similarly sized models at 4-bit quantization, including CPU-only and multi-GPU options, with a user sharing their experience running Minimax 2.7 and Qwen 3.6 on a 5900X + 128GB DDR4 + 7900XT setup.

GLM-5.2, a new flagship model for long-context tasks, supporting 1 million token context, weights open-sourced.

A prediction that open-source AI models will achieve parity with a hypothetical Fable 5 within two months, based on GLM 5.2 benchmark numbers.

ClawCodex, an open-source Python rebuild of Claude Code, now supports Z.ai's GLM-5.2 as a first-class provider, with a demo showing it building a FIFA World Cup 2026 intro page in one shot.

GLM-5.2 has been released with open weights under MIT license, featuring a 1M context window and two reasoning effort modes. Early benchmarks show it performing strongly in coding tasks, making it worth testing beyond benchmark screenshots.

GLM5.2 reintroduces a critic component for fine-grained variance reduction, suggesting that group-based methods are ineffective for long horizons. The author believes OpenAI and Anthropic already use value models.