TokenAssemble
Assemble the right local AI stack for your hardware
TokenAssemble launched on July 21, 2026 with 3 votes, #8,766 of 24,623 launches that month and more than 50% of that year's launches.
What it does
TokenAssemble tells you which local LLMs your GPU, Mac, or mini-PC can run before you download a model or buy new hardware. It evaluates VRAM or unified-memory fit, quantization, context length, expected speed, and runtime compatibility, then gives you a clear verdict and recommended setup for tools like Ollama, LM Studio, llama.cpp, and vLLM.
Check if a GPU, Mac, or mini-PC can run a local AI model with Ollama, LM Studio or llama.cpp. VRAM fit, quantization, context length and speed tiers.
Choose a GPU, Mac, or mini-PC and a model. See whether it fits in VRAM or unified memory, which quantization and context work, how fast it should feel, and which runtime supports it. TokenAssemble connects the parts other tools leave separate. Each step opens the sourced directory behind the verdict. Four complete workflow templates connect software, runtime, and model picks, then grade the hardware underneath. A private Copilot alternative: an editor assistant pointed at a model your own machine serves. A self-hosted ChatGPT-style app for your household or team — nothing leaves the box. Voice notes and meetings to searchable text and summaries, fully offline: a local STT engine feeding a…from tokenassemble.com
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Can your GPU run this LLM?2023 · github.com · ▲15Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization - RahulSChand/gpu_poor
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