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OpenAI launched GPT-4.1, GPT-4.1 mini and GPT-4.1 nano in its API on April 14, 2025. The family targeted software engineering, dependable instruction following, tool calling, image understanding and very large prompts, with a context window of 1,047,576 tokens for GPT-4.1.
GPT-4.1 was later added to ChatGPT during 2025, but OpenAI retired GPT-4.1 and GPT-4.1 mini from ChatGPT on February 13, 2026. GPT-4.1 remains documented as an API model, although OpenAI now recommends evaluating newer GPT-5-family models for many new complex applications.
What OpenAI launched
GPT-4.1 was an API-first release rather than a new ChatGPT subscription tier. OpenAI introduced three related models:
| Model | Original role | Launch input price | Launch output price |
|---|---|---|---|
| GPT-4.1 | Full-size model for coding, agents, instruction following and long-context work | $2 per 1 million tokens | $8 per 1 million tokens |
| GPT-4.1 mini | Smaller, faster and lower-cost model | $0.40 per 1 million tokens | $1.60 per 1 million tokens |
| GPT-4.1 nano | Fastest tier for classification and autocomplete | $0.10 per 1 million tokens | $0.40 per 1 million tokens |
Those are launch prices announced by OpenAI, not a promise that pricing will never change. OpenAI also advertised a 75% discount for cached prompts and a further 50% discount for Batch API requests. Check the current API pricing before budgeting a deployment.
GPT-4.1 launch timeline
- April 14, 2025: GPT-4.1, mini and nano entered the OpenAI API.
- May 2025: GPT-4.1 and GPT-4.1 mini became available in ChatGPT.
- July 14, 2025: OpenAI planned to turn off GPT-4.5 Preview in the API.
- February 13, 2026: GPT-4.1 and GPT-4.1 mini were retired from ChatGPT.
The original announcement is at OpenAI’s GPT-4.1 launch post. The dated API snapshot is identified as gpt-4.1-2025-04-14.
What GPT-4.1 changed compared with GPT-4o
OpenAI positioned GPT-4.1 as a practical improvement rather than simply a larger version number. Its reported advantages included:
- Stronger software-engineering performance, including repository exploration, issue resolution and code editing.
- More reliable adherence to detailed instructions and requested code-diff formats.
- More consistent function calling and tool use.
- A much larger context window and a higher maximum output than the cited GPT-4o snapshot.
- Lower launch token prices than the GPT-4o prices listed by OpenAI.
- A new nano tier for high-volume, low-latency work.
GPT-4.1 is documented as a non-reasoning model. It is designed to respond without a separate extended reasoning stage, which can help latency, but it is not the same category as OpenAI’s reasoning-oriented o-series models.
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| Specification | GPT-4.1 |
|---|---|
| Model IDs | gpt-4.1 and gpt-4.1-2025-04-14 |
| Context window | 1,047,576 tokens |
| Maximum output | 32,768 tokens |
| Knowledge cutoff | June 1, 2024 |
| Input modalities | Text and images |
| Output modality | Text |
| Features | Streaming, function calling, structured outputs, fine-tuning, Batch API, Responses API and Chat Completions API |
The authoritative specification is the GPT-4.1 model page. Although OpenAI discussed multimodal evaluations, GPT-4.1’s directly documented API input is text and images; it is not a native audio- or video-input model. A surrounding application can transcribe or process other media before sending information to it.
How good was GPT-4.1 at coding?
OpenAI reported 54.6% on SWE-bench Verified, compared with 33.2% for the GPT-4o snapshot cited in its announcement. It also reported 52.9% on Aider’s polyglot diff benchmark and 51.6% on Aider’s polyglot whole-file benchmark. Human graders preferred GPT-4.1-generated websites over GPT-4o-generated websites in 80% of the comparisons OpenAI cited.
These are controlled evaluations, not a guarantee that GPT-4.1 will solve 54.6% of every team’s bugs. OpenAI said 23 of the 500 SWE-bench tasks could not run on its infrastructure; counting those as failures would reduce the reported result to 52.1%. Prompts, repository setup, tools, test harnesses and agent scaffolding can materially change results. See the methodology and results in OpenAI’s announcement.
What a one-million-token context window really means
The approximately one-million-token limit lets an application place very large repositories, document collections, support histories or transcripts in one request. That can reduce manual chunking and make cross-file references easier.
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It does not mean the model will retrieve every detail perfectly. OpenAI reported 46.3% on its one-million-token two-needle MRCR test, versus 57.2% on the 128K version. Very large prompts can also add latency, increase token charges and introduce distracting material. Production systems should still rank or filter documents, validate important outputs and test retrieval at the context sizes they expect to use.
GPT-4.1 pricing and cost controls
At launch, GPT-4.1 cost $2 input and $8 output per million tokens; mini cost $0.40 and $1.60; nano cost $0.10 and $0.40. Cached input was priced at $0.50, $0.10 and $0.025 per million tokens respectively. Batch requests received an additional 50% discount under the launch terms.
API billing is usage-based, not a flat ChatGPT subscription. Your bill depends on input and output volume, cache hits, batch processing, retries and tool calls. A ChatGPT Plus plan does not automatically provide API credits.
GPT-4.1 compared with GPT-4o, GPT-4.5 and GPT-5 models
GPT-4.1 versus GPT-4o
OpenAI’s cited comparison gave GPT-4.1 stronger coding and instruction-following results, a larger context window and a higher output limit. The GPT-4o page currently lists $2.50 input and $10 output per million tokens, compared with GPT-4.1’s listed $2 and $8, but prices and model availability can change. Existing GPT-4o applications may still be preferable when their prompts, latency profile, modalities or compatibility have already been validated.
GPT-4.1 versus GPT-4.5
GPT-4.1 was presented as a lower-cost, lower-latency alternative to GPT-4.5 Preview for many developer workloads. The planned API shutdown date for GPT-4.5 Preview was July 14, 2025; this was a launch-era transition plan, not a current availability announcement.
GPT-4.1 versus newer GPT-5-family models
OpenAI’s current model catalog recommends starting with GPT-5 for complex tasks and lists newer options for frontier reasoning, coding, agents and lower-cost workloads. For a new 2026 system, benchmark those models alongside GPT-4.1 rather than assuming the older model is automatically cheaper or better.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to call GPT-4.1 through the API
Prerequisites
- An OpenAI developer account.
- An API key with billing or available credits.
- A current SDK or an HTTPS client.
- Secure storage for the key, such as the
OPENAI_API_KEYenvironment variable.
Minimal Responses API request
curl https://api.openai.com/v1/responses
-H "Content-Type: application/json"
-H "Authorization: Bearer $OPENAI_API_KEY"
-d '{
"model": "gpt-4.1",
"input": "Review this function and identify the most important bug."
}'Use the gpt-4.1 alias when you want OpenAI’s current version of the model. Use gpt-4.1-2025-04-14 when reproducibility requires a fixed snapshot. Pinning a snapshot does not remove lifecycle risk: monitor deprecation notices and maintain a tested fallback.
Is GPT-4.1 available in ChatGPT?
Not as of February 13, 2026. OpenAI retired GPT-4.1 and GPT-4.1 mini from ChatGPT on that date. Their 2025 ChatGPT availability should not be confused with current API access. The retirement details are documented in OpenAI’s ChatGPT model-retirement notice.
Who should still use GPT-4.1?
A sensible fit
- An existing API integration already tested against GPT-4.1.
- A compatibility-sensitive application that benefits from the dated snapshot.
- Code review, repository analysis or document workflows that perform well with its long context.
- Low-latency tool calling, structured output or fine-tuning without an extended reasoning step.
Look elsewhere first
- A new project requiring the strongest current multi-step reasoning.
- A native audio or video application.
- A consumer chatbot experience rather than API deployment.
- A workload that depends on GPT-4.1 nano: the complete catalog currently marks nano as deprecated.
For a new system, test GPT-4.1 against an appropriate current GPT-5-family model on representative prompts, latency targets, failure cases and total cost. Keep retrieval, validation and migration plans even when the model accepts very large contexts.
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