GLM~5.1
PulseAugur coverage of GLM~5.1 — every cluster mentioning GLM~5.1 across labs, papers, and developer communities, ranked by signal.
- developed by Zhipu AI 95%
- instance of Zhipu AI 95%
- instance of GLM-5.2 90%
- developed by GLM-5.2 90%
- developed GLM-5.2 90%
- uses Fireworks AI 90%
- competes with Claude Opus 4-8 80%
- competes with Tencent 80%
- affiliated with Zhipu AI 70%
- competes with GLM-5.2 70%
- competes with Zhipu AI 70%
- used by DeepSeek V4-Pro 70%
- 2026-06-15 product_launch Together AI has launched GLM 5.1, an open-source inference model. source
- 2026-06-09 research_milestone GLM-5.1 achieved a leading score on the SWE-Bench Pro benchmark, surpassing proprietary models. source
- 2026-05-11 product_launch Zai.org open-sourced its GLM-5.1 large language model. source
4 day(s) with sentiment data
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7 PhD students train 7B LLM from scratch using hundreds of AI agents
Seven doctoral students from Beijing Zhongguancun Academy successfully trained a 7B large language model, ZGCM-1, from scratch in just three months. They achieved this by leveraging a team of hundreds of AI agents to ha…
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Open-source ZGCM-1 model achieves high efficiency in math and agentic search
Researchers have introduced ZGCM-1, a 7B parameter foundation model designed for mathematical reasoning and agentic search. The model leverages an efficient training recipe that combines architectural innovations like i…
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Together AI expands fine-tuning with new models and live tracking
Together AI has enhanced its fine-tuning service by incorporating a wider array of open-weight models, including advanced options like GLM 5.3 and Kimi K2.7, alongside cost-effective choices such as Qwen 3.8-27B and Gem…
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Open-source AI models outperform frontier models in cybersecurity tasks
A recent analysis comparing various AI models for cybersecurity tasks found that open-source models significantly outperform frontier models in identifying security vulnerabilities. Across 27 repositories and over 1,600…
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Author adds DeepSeek V4-Pro for unique AI failure modes
The author details a research process for selecting an additional AI model to complement their existing subscriptions, emphasizing the need for models that exhibit different failure modes. After evaluating multiple opti…
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GLM-5.1 (Non-reasoning) achieves 83.9% on GPQA benchmark
A new benchmark evaluation shows that GLM-5.1 (Non-reasoning) achieved an 83.9% score on the GPQA benchmark. This performance was measured independently and highlights the model's efficiency, delivering 13.3 intelligenc…
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AI execution costs plummet, shifting value to imagination and novel problem-solving
The nature of valuable work in software development is shifting as AI models become more capable and execution costs decrease. While routine tasks can be handled efficiently by cheaper models, the most impactful work no…
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AI CTF tournament results challenge model size assumptions
An AI capture-the-flag tournament initially suggested that larger models were superior for security reasoning and multi-step exploitation. However, subsequent, more extensive games involving larger models and different …
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CI check manages Chinese LLM model names and token budgets
A developer has created a CI check to manage the rapidly changing landscape of Chinese LLM model names and their associated token budgets. This tool helps ensure production stability by treating model catalogs as deploy…
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PIVOT method accelerates long-context AI models by optimizing sparse attention
A new method called PIVOT has been developed to optimize the performance of Dynamic Sparse Attention (DSA) models, particularly for handling long contexts. PIVOT addresses a bottleneck in DSA's indexer, which previously…
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MindForge pipeline trains small LLMs for full software engineering lifecycle
Researchers have developed MindForge, an automated pipeline designed to train smaller language models in comprehensive software engineering tasks. This system converts open-source command-line programs into source-free …
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PIVOT indexing method accelerates sparse attention in LLMs
Researchers have developed PIVOT, a novel indexing method designed to optimize token-level sparse attention in large language models. PIVOT addresses the bottleneck created by indexers in systems like DeepSeek Sparse At…
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Zhipu AI's GLM-5.2 leads open-weight models with 1M context window · 1 source tracked
GLM-5.2, a new open-weight model from China's Zhipu AI, has been recognized as the top-performing open model as of July 2026. It achieved a score of 51 in the Intelligence Index v4.1 by Artificial Analysis, placing it f…
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LLM benchmark results reveal performance across multiple models · 9 sources tracked
A recent independent benchmark evaluation has revealed performance metrics for several large language models, including Kimi K2, Sarvam Maya, NVIDIA Nemotron 3 Super 120B, DeepSeek V3.2, Falcon H1R-7B, GLM-5.2, GLM-5.1,…
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New Red Teaming Protocol Finds Hidden Bugs in LLM-Generated Code
Researchers have developed a new protocol called Code Monitor Red Teaming to identify hidden bugs in LLM-generated code that has already passed public tests. The study, which used the CodeMonitorBench benchmark with ove…
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Anomaly launches $10/month OpenCode Go for curated AI coding models
Anomaly has launched OpenCode Go, a $10/month subscription service that provides access to a curated selection of 13 open-source AI coding models. The service aims to offer a reliable and affordable way for developers t…
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Tencent's Hy3 open MoE model beats GLM-5.1 in blind test
Tencent has released Hy3, a 21 billion active parameter open Mixture-of-Experts model that outperformed Zhipu's GLM-5.1 in a blind test. The model, which has 295 billion total parameters and a 256K context window, is av…
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Tencent releases Hy3 model with 295B parameters and 256K context
Tencent has released Hy3, an open-weights AI model with 295 billion parameters, featuring a 21 billion active parameter inference and a 3.8 billion parameter prediction head. The model boasts a 256K context window and u…
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Open-weight LLMs are free to access but costly to run, challenging developers
The article argues that while open-weight large language models (LLMs) are technically free to access, their immense size often makes them prohibitively expensive and difficult to run on standard hardware. Models from Q…
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Tencent's Hy3 model shows strong performance in real-world tasks
The Hy3 benchmark results show the model performing comparably to other advanced models like DeepSeek v4 and GLM-5.1. Tencent's Hy3 achieved a score of 2.67/4 on 312 real-world workflow tasks, outperforming GLM-5.1's sc…