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Articles tagged "Z.ai"

5 articles

AI2026-08-27
GLM-5.3-Flash Requirements — VRAM 190GB to 740GB by Quantization [320B MoE, the Model Behind "Ox Alpha", Aug 2026]
GLM-5.3-Flash needs about 190GB VRAM at 4-bit, 740GB at BF16. VRAM and GPU tables for this 320B/18B open MoE, plus local vs API costs. Updated August 2026.
GLM-5.3Z.aiRequirements
AI2026-08-25
What Is Ox Alpha? OpenRouter's Free 1M-Context Stealth Model
Ox Alpha: free, developer-undisclosed stealth model, ~1M-token context, on OpenRouter/OpenCode since Aug 2026. GLM-5.3 talk runs strong. Updated August 2026.
Ox AlphaステルスモデルGLM-5.3
AI2026-08-15
GLM-5.3 Explained: Z.ai's New Model vs GLM-5.2
GLM-5.3, released Aug 14, 2026, reuses the 743B GLM-5.2 base and gains from post-training alone: a claimed 50% coding jump and top open Terminal-Bench scores.
GLM-5.3Z.aiOpen Weight LLM
AI2026-07-18
GLM-5.2 Requirements Reference — VRAM, RAM & GPU Quick-Lookup Tables by Quantization [753B Open-Weight MoE, 2026]
GLM-5.2 needs roughly 430GB at 4-bit and about 1.5TB at BF16 in combined memory. Quick-lookup VRAM, RAM and quantization tables for running Z.ai's 753B / ~40B-active open-weight MoE (MIT-licensed) locally. Updated July 2026.
GLM-5.2Z.aiRequirements
AI2026-04-10
GLM-5.1 Complete Guide — #1 SWE-bench Pro Open-Source LLM [April 2026]
GLM-5.1 by Z.ai (released April 7, 2026) is the first open-source LLM to top SWE-bench Pro at 58.4%, surpassing GPT-5.4 (57.7%) and Claude Opus 4.6 (57.3%). This guide covers its 744B/40B-active MoE architecture, MIT license, 8-hour autonomous task capability, and setup via Ollama.
GLM-5.1Z.aiSWE-bench