The first Task-Aware MCP server and automated VRAM calculator for LLM fine-tuning. Instantly snipe the cheapest, fastest GPUs across 10+ cloud providers.
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Updated
May 8, 2026 - Python
The first Task-Aware MCP server and automated VRAM calculator for LLM fine-tuning. Instantly snipe the cheapest, fastest GPUs across 10+ cloud providers.
Accurate LLM memory/VRAM calculator — models sliding-window/linear/MoE attention & heterogeneous head_dim where naive calculators are 4–11× off. Apple Silicon + NVIDIA RTX · GGUF · F16/Q8/Q4 KV-cache quant · one MIT file. Powers fitllm.run.
🚀 A lightweight CLI to estimate hardware requirements and quantization compatibility for Hugging Face models.
A collection of serverless, blazing-fast web tools: Docker Compose Generator, LLM VRAM Calculator, NAS RAID Capacity, and Nginx Reverse Proxy Builder.
Anthropic-standard Skill — decide API-vs-self-host LLM costs and fine-tune ROI from any agent context (Claude Code, Cursor, Codex). Live GPU+API prices, deterministic local math.
A CLI tool for estimating GPU VRAM requirements for Hugging Face models, supporting various data types, parallelization strategies, and fine-tuning scenarios like LoRA.
macOS menu bar tool to explore Hugging Face models, detect GGUF/Safetensors configs, and calculate precise VRAM footprint and KV cache overhead.
A lightweight CLI tool to inspect ML checkpoints (.safetensors, .gguf, .pt) and calculate inference VRAM, multi-GPU memory splits, and vLLM serving capacity.
A simple CLI tool to fetch Hugging Face model metadata and estimate required VRAM/RAM for inference.
🖥️ Check if any LLM fits your GPU. VRAM calculator with context-aware fitting, quantization support, and real-time performance estimates.
Optimal GPU, VRAM, and RAM configurations for running DeepSeek R1 locally (7B to 671B models).
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