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The project offers a path to running a large open-weight model for bulk agentic coding tasks without per-token API costs, rate limits, or third-party data exposure, by pairing MCP with rented decentralized GPU compute.
Track this digest for a concise overview of concurrent model releases and Claude Code pricing developments that may affect tooling and cost decisions.
Lavelle Hatcher Jr walks through serving Qwen3.6-35B-A3B — a 35B sparse MoE model scoring 73.4% on SWE-bench Verified — locally with vLLM and wiring it up as a tool-calling coding agent via the OpenAI SDK.