deploy-kimi-k26-on-rtx-pro-6000
CommunityDeploy and serve Kimi-K2.6 with high-performance AI models on NVIDIA RTX PRO 6000 Blackwell GPUs.
Authorsoulmachine
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the deployment and serving of the Moonshot Kimi-K2.6 AI model on NVIDIA RTX PRO 6000 Blackwell GPUs, offering a user-chosen quantization (INT4 QAT or NVFP4) and selecting between vLLM or SGLang engines for optimal performance.
Core Features & Use Cases
- Deploy Kimi-K2.6: Automates the deployment of Kimi-K2.6 (1T MoE, MLA, 256K context, vision) on Linux servers with 8× NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs.
- Quantization and Engine Selection: Allows the user to select INT4 QAT or NVFP4 quantization and choose between vLLM or SGLang engines based on hardware recommendation.
- Official Image Docker Container: Serves an OpenAI-compatible API on port 30000 through an official-image Docker container.
- High-Performance Serving: Achieves high performance with TP=8 and weights bind-mounted in VRAM.
- Productionization: Provides a systemd service and reverse proxy setup for production deployment.
Quick Start
Deploy the Kimi-K2.6 model with INT4 QAT on vLLM on a Linux server with 8× NVIDIA RTX PRO 6000 Blackwell GPUs by running the following commands:
QUANT=int4 FRAMEWORK=vllm bash scripts/serve_docker_vllm.sh
Dependency Matrix
Required Modules
dockernvidia-container-toolkitnvidia-persistencedpython3curl
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: deploy-kimi-k26-on-rtx-pro-6000 Download link: https://github.com/soulmachine/skills/archive/main.zip#deploy-kimi-k26-on-rtx-pro-6000 Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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