Model: GLM-4.7-Flash-Uncensored-Heretic-NEO-CODE

Run the Ultimate Local AI

A comprehensive dashboard to install, configure, and deploy the GLM-4.7 Flash model. Optimized for GGUF quantization to run efficiently on consumer hardware or cloud instances.

Start Installation Cloud Deployment

RAM Requirements

The Imatrix-MAX version is large. We recommend at least 32GB RAM for smooth inference without swapping.

GPU Recommendation

An NVIDIA GPU with 8GB+ VRAM (RTX 3060 or better) allows for acceleration via CUDA.

Storage

The GGUF model typically ranges between 20GB - 40GB depending on the specific quantization (Q4_K_M vs Q8_0).

Automated Setup Script

Generates the command line instructions for KoboldCpp & Ollama

Configuration

1 Thread 8 Threads 32 Threads
Note on Imatrix-MAX

The "Imatrix-MAX" version implies an optimized quantization matrix. Ensure you download the specific .gguf file from the HuggingFace link provided. The script below assumes standard GGUF loading.

root@server:~/glm-deploy
~ $ # Initializing GLM-4.7 Flash Setup...
~ $ git clone https://github.com/ggerganov/llama.cpp
~ $ cd llama.cpp && make
~/llama.cpp $ ./llama-server \
--model ./models/glm-4.7-flash-uncensored.Q4_K_M.gguf
--n_ctx 4096 --n_gpu_layers 35
--port 8080 --host 0.0.0.0
[INFO] Server starting on http://localhost:8080
* Adjust --n_gpu_layers based on your VRAM capacity.

Cloud Deployment Options

Running this model in the cloud requires instances with high RAM and VRAM.

RunPod

Best for short bursts. Use an A100 or H100 pod. Upload your GGUF file to Pod Storage and run the server.

nvidia-a100-80gb
Pay per second
Launch Pod

Vast.ai

Marketplaces for GPU instances. Look for "RTX 4090" or "A100 80GB" instances. Very cost-effective.

96GB RAM + 24GB VRAM
Bid/On-demand options
Browse Instances

Lambda Labs

User-friendly interface. Good for A10s and H100s. Easy to set up SSH and transfer models.

H100 80GB or A100 40/80GB
Flat rate pricing
Get API Key

Quick Cloud Setup Checklist

  • Select Instance: Ensure instance has > 32GB System RAM AND > 16GB VRAM for the Imatrix-MAX version.
  • Download Model: Use `wget` or `huggingface-cli` on the cloud instance to download the GGUF file directly to storage.
  • Start Server: Run the `llama-server` command with `--host 0.0.0.0` to allow external web access.