Choosing a Coding-Agent Model in 2026
A Task-Based Framework for Capability, Accepted-Task Cost, Controls, and Provider Compatibility
By
Tenten AI Research
ML Engineering
Published
Updated
Read time
6 min
Abstract
Select a coding model for a defined workload, runtime and acceptance standard. Compare completed, accepted tasks alongside cost, latency, tool behavior, data requirements and review effort. A public benchmark helps form a shortlist; your repository and operating constraints determine whether a candidate is suitable.
The original May 2026 publication named models that had already been released: Claude Opus 4.7 on 16 April, GPT-5.5 on 23 April and Gemini 3.1 Pro Preview. These are dated candidate examples, not an up-to-date ranking. Their provider-reported capabilities and settings should be checked against the version being evaluated. This guide develops the selection method without assigning a universal winner or an unmeasured cost advantage.
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