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Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-04-28 · Source: legacy_model_catalog
Code generation, refactoring and review, and developer-tooling workloads with large context.
GPT-5-Codex is a specialized version of GPT-5 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering ta...
gpt-5-codex is a Code model from OpenAI (US). HotON.ai tracks it at $1.25 per 1M input tokens and $10.00 per 1M output tokens, with a 400K-token context window. Its composite efficiency score is 87/100 at an estimated $0.008 per successful task.
gpt-5-codex is tracked at $1.25 per 1M input tokens and $10.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $7.81 per 1M tokens. Figures are illustrative demo data.
Code generation, refactoring and review, and developer-tooling workloads with large context.
gpt-5-codex supports up to a 400K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, gpt-5-codex is cheaper than 22% of models on input price and ranks #442 of 535 by overall efficiency.
Yes — qwen3-coder-flash is a lower-cost option at $0.98 per 1M output tokens, while still covering similar Code use cases. Compare them side by side on HotON.ai.
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HotON.ai — gpt-5-codex (OpenAI): $1.25/1M input, $10.00/1M output, as of 2026-04-28. https://hoton.ai/en/models/openai-gpt-5-codexPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.