Loading...
Loading...
Found 9 Skills
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
Novita AI: LLM, Image Generation & Editing, Video Generation, Audio (TTS/ASR), and GPU Cloud. Use this skill whenever the user wants to call Novita AI APIs — chat with LLMs (DeepSeek, Llama, Qwen), generate images (FLUX, Stable Diffusion, Seedream, Hunyuan Image), edit images (remove background, upscale, inpainting, img2img, outpainting, reimagine, merge face, replace background, remove text), generate videos (Kling, Wan, Hunyuan, Minimax Hailuo, Vidu, PixVerse, Seedance), do text-to-speech or speech-to-text (MiniMax TTS, GLM TTS, Fish Audio, ASR, voice cloning), run OpenAI-compatible batch jobs, manage GPU cloud instances and serverless endpoints, or check account balance and billing. Also trigger when the user mentions novita.ai, Novita AI, Novita API key, or wants to use any Novita platform service — even if they just say "generate an image" or "run an LLM" and Novita is available as a provider.
Vast.ai API Documentation - Affordable GPU Cloud Marketplace
Create serverless endpoint templates and endpoints on RunPod.io. Supports Python/Node.js runtimes, GPU selection (3090, A100, etc.), and idempotent configuration. Use this skill when a user wants to set up a new serverless endpoint or template on RunPod.
Answer what is available, what fits and the price against Runpod's catalogs: GPU and CPU types with price, live stock per data center and per product, the CUDA versions that have capacity, the Hub worker marketplace, the public template catalog, and the pay-per-use Public Endpoints. Read-only: it filters to the user's real constraint, sizes a model's VRAM need against real stock, quotes price and stock from the reads, and says "none found" rather than inventing an entry. Use when the user asks a catalog, sizing, availability or price question that does not ask to create anything through the Runpod MCP tools.
Bring any source (a HuggingFace repo, a ComfyUI workflow, a Hub release, a custom container image, a GGUF repo, a Civitai asset, or a community template) to a proven Runpod Serverless endpoint: pick the engine for the modality and model format, size the GPU from the model's real metadata, provision, warm, prove it with one real job, and hand back the URL with what it bills. Deploys an existing source through the Runpod MCP tools; code-first Python deploys (the Flash dev loop) are out of scope. Use when the user wants a model or worker served on Runpod Serverless, whatever the modality: text generation, speech-to-text or text-to-speech, image or video generation, embeddings, document processing, or their own handler image.
Provision a Runpod Pod for interactive, development or training use and tell the user exactly how to connect to it. Reads stock before creating, picks the image and GPU class from the catalog reads, exposes only the ports the workload needs, hands back the working proxy URL or SSH address, and for training co-locates a network volume so checkpoints outlive the Pod. Also covers creating a Pod and stopping it immediately, so that only its disk bills until the user comes back. Use when the user wants a GPU or CPU machine of their own (a web app, Jupyter, SSH, a training box) rather than a Serverless endpoint, through the Runpod MCP tools.
Manage CompShare GPU cloud resources through the compshare CLI. Use when Codex needs to install or configure compshare-cli, search GPU specifications and inventory, inspect pricing, create or manage instances, connect over SSH, transfer files, run durable remote jobs, manage images, disks, US3, teams or billing, ask product questions, or diagnose CLI problems.
Create or improve a complete Runpod template project from an application request, local code, or GitHub repository, with a documented Dockerfile and app-specific files for Pods or queue/load-balanced Serverless. Use runpod-templates for finding or operating existing official templates, runpod-mcp/runpodctl to register an already-built image as a template, flash for its code-first workflow, and companion-clis for standalone image build/push commands.