Launch GLM-4.7-Flash with 1M Context

Deploying this model locally is quickest when done via Docker.

Make sure to follow the instructions below.

The installer auto-downloads and deploys the entire model pack.

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

🔍 Hash-sum: e16db7a6ce7d355e8de7b06114934f6a | 🕓 Last update: 2026-06-23 Verify Processor: next-gen chip for heavy context processing RAM: minimum 16 GB for stable 8B model loading Disk: high-speed SSD 120 GB to cache model layers Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The GLM-4.7-Flash model delivers exceptionally fast inference while maintaining high accuracy across a broad range of language tasks. Built with a parameter count of 26 billion and a context window of 128 k tokens, it balances size and efficiency for both research and production environments. Its training leverages a diverse corpus of web‑scale text and multimodal data, enabling robust understanding of images, code, and natural language queries. The model incorporates optimized attention mechanisms that reduce latency, making real‑time applications such as chat assistants and content generation seamlessly responsive. Compared to earlier GLM versions, GLM-4.7-Flash shows notable improvements in factual consistency and reasoning speed, as highlighted in the following comparison table.

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