Model detail
gpt-4.1
GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks. It is tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.
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
$2.0000 /1M Tokens
Completion
$4.0000 /1M Tokens
Cache read
$0.5000 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Long-context reasoning and software engineering
Use GPT-4.1 for tasks requiring a 1M token context window, including long-document analysis, complex codebases, and enterprise knowledge retrieval. It excels at instruction following and agent reliability.
What should you check before using it?
Plan for the 1M context window and instruction-following needs
Confirm your workload benefits from the 1M token context window. Test instruction-following accuracy on your specific prompts and verify agent reliability for your most demanding workflows.
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 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 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o across coding and instruction compliance benchmarks.
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.