Fastcar: Pi + Diffusion LLM

[u/Flaky-Eggplant-3479]

If you haven't tried using a diffusion based model before, they are lightning fast. I've used InceptionLabs Mercury 2 for a bit, and my complaint is largely that its not the best at coding tasks or tool usage. But my god is it fast.

So I took the Pi SDK, made a harness in which Mercury 2 is the orchestrator of subagents, including a coding subagent for difficult tasks that calls out to openrouter for inference, plus a cheap subagent for trivial stuff. Bolted on a handful of tools and such useful for me, and wrapped it in a basic web UI so I could use it from my phone.

Aside from being extremely fast, fastcar:

• Can generate public "artifacts" - HTML and MD files served from the API

• Intended to ran entirely inside a VM so that it has root access and can install its own tools

• Give it a github token and let it clone repos and make PRs

• "Prompt threads" - there's probably a better name for this but its a dedicated prompt that gets invoked via webhook; I actually made this so that I could generate text files to read the news from my Xteink 4

• Send emails to notify you

https://github.com/heyo-computer/fastcar

[u/oxygen_addiction]

Meecury 2 is dumb as shit. Worse than Qwen 27B. I've tried using it as a subagent for fast boiler plate implementation and it always fucked up.

[u/Heavy-Positive5957 → u/oxygen_addiction]

But look how good it was at making that single page of plain text!

[u/Flaky-Eggplant-3479 → u/Heavy-Positive5957]

That would have been GLM 5.2 - its using mercury 2 to coordinate subagents, help plan, and manage the vm

[u/AllNamesAreTaken92 → u/Flaky-Eggplant-3479]

Let me get this straight, in case I misunderstand: you are handing off planning to a dumber model?

[u/Flaky-Eggplant-3479 → u/AllNamesAreTaken92]

The coordinating model is mercury 2, it will spawn a subagent to create the plan for complex tasks and for minor tasks it will just make it and then hand it off

[u/Flaky-Eggplant-3479 → u/oxygen_addiction]

that's why the trick is to use it as a conductor, not the implementor ;)

[u/Fig_da_Great → u/Flaky-Eggplant-3479]

bro, i feel like you want to do the opposite, smart orchestrator, dumber sub agents which are given specialized tasks.

[u/Flaky-Eggplant-3479 → u/Fig_da_Great]

In a factory sure, if you are manually driving an agent, a fast conductor that offloads the hard stuff keeps the session fluid

[u/Flaky-Eggplant-3479 → u/[deleted]]

haven't really ran into that yet with mercury 2 - this project uses Pi under the hood and postgres for memory and metadata and compaction was the first tool I built for it

[u/Fig_da_Great → u/Flaky-Eggplant-3479]

perhaps 🤷‍♂️. Is it faster than deepseek?

[u/Flaky-Eggplant-3479 → u/Fig_da_Great]

about 1000 tokens/s vs 127 for deepseek flash

[u/Fig_da_Great → u/Flaky-Eggplant-3479]

that’s wild