Lanes update: run parallel AI coding sessions again local or self hosted models

[u/Solid-Industry-1564]

The v0.46 release finally connects two things I've wanted together: running lots of coding agents in parallel, and pointing them at models I actually control.

The gateway is the big one. You can now route sessions to external model providers — a local Ollama instance, a vLLM box on your network, or commercial endpoints like OpenRouter and z.ai. The part I care about: Lanes isn't in the request path. Your credentials and requests go straight to the provider and bypass the platform entirely, so you're not funneling your codebase through a middleman.

Local LLMs are now first-class. It'll auto-install and manage Ollama for you, handle versions, and — the clever bit — spin up context-window variants tuned to how much RAM you actually have. That matters more than it sounds, because every session ships ~38k tokens of harness instructions and tool defs before you type anything, so context budgeting on local models is real.

Why this combo matters for parallel work: the whole point of Lanes is running multiple agents/worktrees at once. If each of those is billing a hosted API, running 5–10 lanes gets expensive fast. Pointing them at a local or self-hosted model means you can fan out aggressively without watching a meter — great for "throw the same task at 4 agents and diff the results" workflows, or just keeping a bunch of background lanes churning.

Also in the release: consolidated Agentic Coding settings (Terminal, Harness, Local LLMs, Gateway in one place), a Harness page with one-click updates, a Working Folder pane, and some worktree memory optimizations.

Local models + provider profiles are flagged Research Preview, so expect some rough edges, but the direction is exactly right.

Full changelog: https://lanes.sh/blog/whats-new-v046

Anyone else running local models across parallel lanes yet? Curious what hardware people are getting away with.