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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
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.
Devstral Medium is a high-performance code generation and agentic reasoning model developed jointly by Mistral AI and All Hands AI. Positioned as a step up from Devstral Small, it achieves...
devstral-medium is a Code model from Mistral AI (US). HotON.ai tracks it at $0.40 per 1M input tokens and $2.00 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 88/100 at an estimated $0.002 per successful task.
devstral-medium is tracked at $0.40 per 1M input tokens and $2.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $1.60 per 1M tokens. Figures are illustrative demo data.
Code generation, refactoring and review, and developer-tooling workloads with large context.
devstral-medium supports up to a 131K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, devstral-medium is cheaper than 47% of models on input price and ranks #416 of 537 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 — devstral-medium (Mistral AI): $0.40/1M input, $2.00/1M output, as of 2026-04-28. https://hoton.ai/en/models/mistralai-devstral-mediumPricing 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.