Model detail
o3-mini 20250131
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to "high". The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities. The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.
Model specs
- Model ID
-
o3-mini-2025-01-31
- Context length
- 200K
- Max output
- 100K
- I/O modalities
- Released
- 2025-01
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$1.1000 /1M Tokens
Completion
$4.4000 /1M Tokens
Cache read
$0.5500 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Cost-efficient STEM reasoning with adjustable effort
Use o3-mini for science, math, and coding tasks where you need strong reasoning at lower cost. It supports adjustable reasoning_effort (low/medium/high) and matches o1 performance on AIME and GPQA at medium effort.
What should you check before using it?
Tune reasoning_effort for your task
Set reasoning_effort to low, medium, or high based on task complexity. Test function calling and structured outputs. Note that o3-mini does not support vision processing. Knowledge cutoff: 2023-10-01.
Why use it through MixRoute?
o3-mini keeps its 200,000-token context on one route
The full 200,000-token context stays reachable on the same route. MixRoute serves o3-mini on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID o3-mini-2025-01-31 and re-run your integration tests.
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Capabilities & compatibility
Unconfirmed capabilities stay "Unknown," no guesses
Tool calling
o3-mini supports function and tool calls.
tools definition; the response returns tool_calls to execute and feed results back.
Structured output
o3-mini can produce JSON-formatted output on demand.
response_format: { type: "json_schema" } forces valid JSON output.
Streaming
o3-mini supports streamed responses.
stream: true streams tokens incrementally, so chat UIs render as they arrive.
Prompt caching
o3-mini supports prompt caching under supported routing conditions.
OpenAI SDK
Call o3-mini through MixRoute's OpenAI-compatible endpoint.
base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
Share of the same prefix read repeatedly, up to 100%
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FAQ
Compare o3-mini-2025-01-31 against models of similar capability and pricing on your actual workload. Evaluate latency, output quality, instruction following, and cost per task. Run side-by-side tests with your own prompts — the best model depends on your specific use case, not just benchmark scores.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.