AI language model for text generation and analysis.
Price per 1 million tokens
per 1M tokens you send
per 1M tokens you receive
Input tokens represent the text you send to the model for processing. Output tokens represent the model's generated response. Pricing is set by OpenRouter and reflects current API rates as of October 2025.
per month
per month
per month
Devstral Small 1.1 (OpenRouter) by OpenRouter is a code‑savvy AI model for pair programming, generation, and refactoring.
OpenRouter
Text
Text-only processing
131072 tokens
Maximum tokens per request
$0.10
per 1M input tokens
$0.30
per 1M output tokens
Devstral Small 1.1 (OpenRouter) is a large language model from OpenRouter designed for real‑world applications where speed, quality and cost all matter. It’s priced at $0.10 per million input tokens and $0.30 per million output tokens, so teams can estimate usage‑based spend with simple math.
The model supports a context window of about 131,072 tokens, which is enough for long chats, multi‑document prompts, or passing rich system instructions without constant truncation.
Engineering teams typically reach for this model when they need reliable code suggestions, test generation, and refactors that preserve intent. It handles mixed natural‑language and source‑code prompts gracefully, and can follow file‑level or repository‑level style guides when provided.
In stack choices, many teams compare Devstral Small 1.1 (OpenRouter) against Claude 3.5 Sonnet. The trade‑off usually comes down to latency tolerance, budget per request, and whether you need image understanding or deeper chain‑of‑thought style reasoning. If you’re cost‑sensitive, keep prompts concise, cache system instructions, and stream outputs so users perceive faster response. If quality is the priority, add brief exemplars and explicit success criteria in the prompt; small guidance often yields outsized gains.
For production, pair the model with guardrails (content filters, schema validators) and log prompts/responses for offline evaluation. Finally, create simple comparison tests—five to ten representative tasks from your app—to verify this model’s answers, latency and cost against your alternatives before you commit. To control spend, consider tiering workloads: route routine queries to a cheaper sibling and reserve this model for complex or customer‑visible moments. Add retries with temperature control, and prefer JSON‑mode or tool calling for structured outputs that slot directly into your pipeline without brittle parsing.
Devstral Small 1.1 (OpenRouter) is a AI model from OpenRouter. It’s tuned to read and generate source code, follow instructions, and transform files. Pricing is $0.10 per 1M input tokens and $0.30 per 1M output tokens. The context window is roughly 131,072 tokens, allowing long prompts and documents. Common uses include chat assistants, summarization, knowledge search, report drafting, and, when supported, image understanding or tool use. It integrates well into web apps, backends, and automation pipelines where latency and reliability matter.
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