When to Choose Each Option
Clear guidance based on your specific situation and needs.
Our Recommendation
A 30-task eval on DeepSeek V4 Pro (max reasoning) via Composio: pi solved 21/30 tasks, Codex 20/30 — at identical cost per shared success ($0.031). But Codex burned ~2.4x fewer tokens per task (383,722 vs 924,990; pi averaged 16.3 turns and kept going). On Databricks' multi-million-line benchmark (Opus 4.8, xhigh), pi had the highest pass rate of all harnesses tested at ~3x less context per turn and roughly half the cost of Claude Code and Codex. Lesson: lean overhead does not automatically mean lean sessions — thin harnesses win only when the model needs fewer turns. Pricing axis: pi is free, you pay your model provider directly via subscription OAuth or API keys (Anthropic subscriptions work out of the box; local, DeepSeek and GLM tier routings stay available); Codex plans meter requests — roughly 20 Codex requests per month on the $20 Plus plan and ~900 on the $200 Pro plan, shared across CLI and desktop. Decision: pick Codex for overnight, unattended and parallel delegation (sandbox, cloud, subagents and CI/Slack workflows are built in, and the models know the harness); pick pi when cost-per-task, auditability and model sovereignty outrank vendor loyalty — transparent loop, model swap per keystroke, verification loops are your own TypeScript build. Neither winner is permanent: as of 29 Sep 2026 pi added MCP in its core (Codemode), reversing its famous "no MCP" stance — exactly why you should benchmark your own ten tasks before committing. Related glossary: [Agent Harness](/glossary/agent-harness), [Model Context Protocol](/glossary/model-context-protocol), [Context Engineering](/glossary/context-engineering).
- Choose Pi when...
- Choose Codex CLI when...