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OpenMake LLM
Local-first AI workspace for your models and tools
Open-source, self-hosted AI workspace for local and open-weight models. Route vLLM/LiteLLM, run autonomous agents in persistent Docker sandboxes, connect MCP tools, do cited Deep Research, create exportable artifacts, and enable external models only with your own keys.
Hi Product Hunt — OpenMake is not a company. We are a small team that enjoys open-source software, open hardware, and running services on machines we control.
We built OpenMake LLM because local-model support often feels bolted onto cloud-first products. We wanted local and open-weight models to be the normal path, with every external provider remaining an explicit BYOK choice.
Our real development setup is a Mac mini running OpenMake, PM2, and a loopback-only LiteLLM gateway, paired with an NVIDIA DGX Spark powered by the GB10 Grace Blackwell Superchip. The DGX Spark serves private Qwen, BGE, and FLUX vLLM endpoints over Tailscale. This is our test setup, not a hardware requirement; any compatible OpenAI-style endpoint can replace it.
Normal chat resolves one model and shares one provider-gated MCP tool loop. Multi-agent Discussion is an explicit mode rather than something invoked for every prompt. Autonomous tasks run shell, Python, browser, and file tools inside persistent Docker sandboxes with checkpoints, manual resume, and human approval boundaries. Deep Research keeps citations, and results can become HTML, PDF, or DOCX artifacts.
OpenMake LLM is MIT licensed and still not a one-click lightweight install. Today it needs Node.js 24, Docker, PostgreSQL, and an OpenAI-compatible model endpoint. Local vLLM also needs enough compatible GPU memory.
We would especially value feedback on installation, working GPU/model combinations, role-based model routing, and which agent actions should always require human approval.
Source and real screenshots: https://github.com/openmake/open...
Website: https://openmake.cc/en/?utm_sour...
Live demo: https://chat.openmake.cc
About OpenMake LLM on Product Hunt
“Local-first AI workspace for your models and tools”
OpenMake LLM was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #94 on the daily leaderboard. Open-source, self-hosted AI workspace for local and open-weight models. Route vLLM/LiteLLM, run autonomous agents in persistent Docker sandboxes, connect MCP tools, do cited Deep Research, create exportable artifacts, and enable external models only with your own keys.
On the analytics side, OpenMake LLM competes within Open Source, Artificial Intelligence and GitHub — topics that collectively have 585.9k followers on Product Hunt. The dashboard above tracks how OpenMake LLM performed against the three products that launched closest to it on the same day.
Who hunted OpenMake LLM?
OpenMake LLM was hunted by Jae Sang Lee. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of OpenMake LLM including community comment highlights and product details, visit the product overview.
Jae Sang Lee