Model detail
gpt-4.1-mini
GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard instruction evals, 35.8% on MultiChallenge, and 84.1% on IFEval. Mini also shows strong coding ability (e.g., 31.6% on Aider’s polyglot diff benchmark) and vision understanding, making it suitable for interactive applications with tight performance constraints.
Model specs
- Context length
- 1.047576M
- Max output
- 32.768K
- I/O modalities
- Text / Image
- Released
- 2025-04
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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
$0.4000 /1M Tokens
Completion
$0.8000 /1M Tokens
Cache read
$0.1000 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Cost-efficient long-context tasks with strong instruction following
Use GPT-4.1 Mini for interactive applications that need the 1M token context window at lower cost. It delivers competitive coding and instruction-following performance with substantially lower latency than GPT-4.1.
What should you check before using it?
Confirm performance meets your task requirements
Test your specific coding and instruction-following tasks. GPT-4.1 Mini trades some capability for speed and cost—verify it meets your accuracy thresholds before committing to production.
Why use it through MixRoute?
Use the OpenAI-compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID gpt-4.1-mini through MixRoute, then run the same integration tests used for the current client.
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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
GPT-4.1 Mini is a mid-sized model in the GPT-4.1 series, delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and shows strong coding and instruction-following ability.
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.