Roundup
Best AI Models for Coding
Which frontier models actually hold up in multi-file refactors, agentic tooling and test-driven work, and what they cost per million tokens.
Coding is the workload where model choice changes your bill the most. Agentic tools such as Copilot, Cursor and Claude Code re-send large context on every step and generate long diffs, so output pricing and reliability (fewer retries) matter more than headline capability.
We weigh three things: how well a model plans and executes across several files, how often it needs a second attempt, and the blended price at a coding-typical 3:1 input-to-output ratio. Prices below are live from OpenRouter.
Strengths
- Anthropic's Claude family remains the most dependable in long agentic sessions and multi-file changes.
- OpenAI's GPT-5 line is excellent at precise, surgical edits and generates strong unit tests.
- Open-weight options from DeepSeek and Qwen are a fraction of the price and more than adequate for bulk or background tasks.
Watch out for
- Frontier Claude and GPT models are among the most expensive per output token on the market.
- Cheaper models need tighter prompting and more review; savings can evaporate if you spend the time re-checking output.
- Context limits still bite on large monorepos; retrieval and file selection matter more than raw window size.
Best for
Verdict
Use a frontier Claude or GPT model for anything you will ship and let an open-weight model handle the grunt work. Check the live blended price on the AI Tracker before committing to a provider for a heavy workload.
