OpenAI
GPT-6.1 Sol
gpt-6.1-sol
Total Context
1.1M
Max Output
128K
Released
N/A
Input$2 / M tokens
Output$10 / M tokens
GPT-4.1
gpt-4.1GPT-4.1 is an OpenAI model generation focused on improved coding, instruction following, and long-context performance. Official announcements present it as a stronger developer model than GPT-4o for many programming and instruction-heavy tasks. Its catalog description should highlight practical coding reliability and long-context understanding.
Context Window
1M tokens
Maximum Output
32.8K tokens
Release Date
Apr 14, 2025
Modalities
GPT-4.1 Pricing
| Input Price | Output Price | Cache Read |
|---|---|---|
| $2/M | $8/M | $0.5/M |
GPT-4.1 API Capabilities
Reasoning
Not supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Supported
Knowledge Base
2024-04-01
Endpoint Protocols
geminiCompletions APIMessages API
GPT-4.1 Model Highlights
GPT-4.1 combines literal instruction following, strong coding and million-token context with low-latency responses that omit a reasoning phase.
Precise Instruction Following
Follows explicit prompts closely and literally, giving developers detailed control over task behavior and output requirements.
Million-Token Context
Supports a 1,047,576-token context window for processing large codebases, document collections and extensive reference material.
Low-Latency Coding
Performs code generation and analysis without a separate reasoning phase, supporting responsive developer interactions.
GPT-4.1 Use Cases
GPT-4.1 fits repository analysis, long-document processing and responsive applications with explicit, detailed instructions.
Repository Analysis
Reads large collections of source files to map dependencies, explain architecture and identify locations for planned changes.
Long Document Processing
Processes extensive document collections to extract requirements, compare passages and generate structured summaries.
Instruction-Driven Automation
Executes clearly specified business or developer workflows and returns outputs that follow detailed formatting and content rules.
How to Use GPT-4.1 via the TokenHub API
Replace these path values before running: {model}
curl 'https://us-api.tokenhub.com/v1beta/models/{model}:generateContent' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY"GPT-4.1 Benchmarks
GPT-4.1
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 19.4 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 21.8 |
| Artificial Analysis Math Index | Artificial Analysis math reasoning aggregate | 34.7 |
| Knowledge & Reasoning | ||
| MMLU-Pro | Advanced multi-task knowledge | 80.6% |
| GPQA | Advanced science problem solving | 66.6% |
| HLE | Broad expert-level exam set | 4.6% |
| Coding & Engineering | ||
| LiveCodeBench | Live coding problems | 45.7% |
| SciCode | Scientific coding challenges | 38.1% |
| Terminal-Bench Hard | Hard terminal task execution | 13.6% |
| Math | ||
| MATH-500 | Advanced math problem solving | 91.3% |
| AIME | Competition math problems | 43.7% |
| AIME 2025 | Competition math problems | 34.7% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 43.0% |
| AA-LCR | Long-context reasoning | 61% |
| τ²-Bench | Agent workflow tasks | 47.1% |
Metrics sourced from Artificial Analysis
Frequently asked questions about GPT-4.1
Understand what GPT-4.1 is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
What is GPT-4.1, and where does it fit in OpenAI’s model lineup?+
GPT-4.1 is a high-capability, non-reasoning GPT model focused on instruction following, tool use, and long-context work. It has been retired from ChatGPT, while API availability may remain; check TokenHub’s current listing.
Which workloads are the best fit for GPT-4.1?+
Best-fit scenarios include working across large codebases, strict instruction following, and tool-enabled application workflows. Test representative inputs and define measurable acceptance criteria before production.
Why might a team select GPT-4.1 over a smaller or older model?+
Key strengths include strong handling of long context, reliable adherence to detailed instructions, and effective use of tools and function calls. This combination is especially useful for strict instruction following.
What should be validated before relying on GPT-4.1?+
Consider another model when the task needs the deepest deliberate reasoning, very low latency is the main requirement, or the workflow cannot include human review for important decisions. Run generated code through tests, security checks, and human review before merging or deployment.
What is the practical TokenHub setup guidance for GPT-4.1?+
In TokenHub, select the exact model identifier displayed for GPT-4.1, use the endpoint documented for your account, and authenticate with your TokenHub credentials. Confirm whether the TokenHub entry exposes the input types, tool behavior, and output controls your application needs.
Ready to use GPT-4.1?
Use one API key to access GPT-4.1 and more AI models through TokenHub.
Media and Discussions
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