
Chameleon
Run any LLM on demand — zero idle VRAM.
What it does
Chameleon is a stateless AI runtime that becomes any LLM on demand. Instead of keeping models loaded, it routes each request to the best model, loads it just-in-time, executes, and fully unloads — resulting in zero idle VRAM usage. Run multiple models efficiently with one runtime, without wasting memory or restarting systems.
Does the same job
all alternatives →- TVTiny-vLLM – high performance LLM inference engine in C++ and CUDAMay 2026 · github.com · ▲205


- TLTiny LLMs – Browser-based private AI models for a wide array of tasks2023 · tinyllms.vercel.app · ▲142
- WMWe made glhf.chat – run almost any open-source LLM, including 405B2024 · glhf.chat · ▲161
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
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Launched alongside, April 2026
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Thought the resources for GPU arch were lacking, so here we are
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