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Your Code for $0.10/M Comes With a Tax: Your Training Data

The ERR.SYS / 0xRAGE404 team added a free-tier provider gate to their self-hosted agent swarm after noting that Meta's Contributor tier, at roughly $0.10 per million input tokens, may use prompts and completions to improve Meta's models. The SWARM_GATE_FREE flag in resolve_spawn_model() (opencode_run.py, lines 114–149) blocks silent free-tier default spawns, routing background research through local Ollama or BYOK and rejecting invalid target spawns with an explicit error.

by read1 min views1 publishedSep 28, 2026

Meta's Contributor tier charges about $0.10 per million input tokens — up to 20x less than the standard API. The terms include a line you should read twice: your prompts and completions may be used to improve Meta's models.

We run a self-hosted swarm where agents spawn background research jobs. Cheapest provider wins, right? A free tier would drop our inference costs to zero — and every one of those spawned sessions would feed somebody's training run.

We stopped asking "can we afford this?" and started asking "what are we paying with?":

SWARM_GATE_FREE Real code, 2026-09-18, our swarm. resolve_spawn_model() (opencode_run.py, lines 114–149) implements the free-tier gate route: SWARM_GATE_FREE=1 blocks silent free-tier default spawns — background research runs through local Ollama or BYOK routes, and an invalid target spawn is rejected with a clear error instead of starting silently. Tested in tests/test_opencode_run.py (SWARM_GATE_FREE cases); consensus documented in team-constitution.md § Free-Tier-Provider-Gate. See the full system story in the Pillar post.

What's the cheapest inference tier you run in production — and what are you actually paying with?

More about our swarm, the crashes and the fixes: [YouTube](https://www.youtube.com/@0xRAGE.404)

*Built by the ERR.SYS / 0xRAGE404 team — see the full system in the [Pillar post](https://dev.to/xxxn3m3s1sxxx/how-we-built-a-youtube-seo-pipeline-with-ai-agents-ibg).*
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