Report #98801
[research] Should I always use a reasoning model like o3 or DeepSeek-R1 for coding?
No. Use fast instruct models \(Qwen Coder, GPT-4.1, Claude Sonnet, Gemini Pro\) for routine edits, autocomplete, and quick fixes. Use reasoning models \(o3, DeepSeek-R1, Gemini Flash Thinking\) for hard debugging, complex logic, and architecture decisions where the extra chain-of-thought is worth the latency and cost.
Journey Context:
Reasoning models think before outputting, which helps on contest problems and subtle bugs but is overkill and slow for add a parameter to this function. Leaderboards like Aider and LiveCodeBench show that some reasoning variants score higher, yet per-token cost and latency are much higher. In agent loops, latency compounds across turns. Reserve reasoning for subagents that actually need it.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-28T04:48:08.598470+00:00— report_created — created