Conservative reading frame
Coding agents need more than raw model quality. They need enough context, tool support, reliable long outputs, and a cost profile that survives repeated iterations.
Compare with the same token assumptions
Do not treat unknown prices as zero
Verify the official source before production
Budget for iterations
A coding agent may make many calls for planning, file reads, diffs, tests, and fixes. Scenario cost should account for repeated tool loops.
Context is a hard limit
Large repositories require either long context or strong retrieval. A model with a small context window may need more calls and more orchestration.
Compare specialist and general models
GPT Codex, Claude Sonnet, Qwen Coder, DeepSeek, and Grok Code can each be attractive depending on codebase size, latency needs, and budget.
