Multi-model coding agents: real savings or just complexity? One dev's Codex + DeepSeek stack
zer0_level · reddit · 2026-11-07
A developer shares a multi-model coding agent stack: Codex/ChatGPT for architecture, planning and reviews; OpenCode + DeepSeek V4.1-Fast for implementation (beat GLM, Qwen, Kimi in his tests); Serena, ast-grep and other tools for codebase navigation. Pain point: strong models burn subscription limits fast (Codex eats a 5-hour allowance in 30 minutes) while cheap models need too much supervision. He's evaluating orchestration tools (Ruflo, OpenCode Ensemble, Agent Deck) and context/memory tools (TokenEconomizer, Hindsight), and asks the community five questions: multi-model vs single agent, orchestration choices, MCP/memory/context tooling, observability across agents, and whether anyone has a truly autonomous description-to-tested-code workflow.
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