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 Mini
gpt-4.1-miniGPT-4.1 Mini brings the GPT-4.1 family’s coding and instruction-following improvements into a faster, lower-cost form. It is suitable for high-volume developer tools, structured generation, extraction, and product features that do not require the full model. The main distinction is production efficiency while retaining the 4.1 generation’s task discipline.
Context Window
1M tokens
Maximum Output
32.8K tokens
Release Date
Apr 14, 2025
Modalities
GPT-4.1 Mini Pricing
| Input Price | Output Price | Cache Read |
|---|---|---|
| $0.4/M | $1.6/M | $0.1/M |
GPT-4.1 Mini API Capabilities
Reasoning
Not supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Supported
Knowledge Base
2024-04-01
Endpoint Protocols
Completions APIMessages APIgemini
GPT-4.1 Mini Model Highlights
GPT-4.1 Mini combines precise instruction following, million-token context and low-latency text and image processing in a smaller model.
Precise Instruction Following
Follows explicit requirements closely, helping applications produce consistent behavior and outputs under detailed prompts.
Million-Token Context
Supports a 1,047,576-token context window for processing large document sets, code collections and extensive reference material.
Low-Latency Multimodality
Processes text and image inputs without a separate reasoning phase, supporting responsive visual and document applications.
GPT-4.1 Mini Use Cases
GPT-4.1 Mini fits responsive document analysis, high-volume coding assistance and image-aware information extraction.
Large Document Analysis
Reviews extensive document collections to extract requirements, compare sections and prepare structured summaries.
High-Volume Code Assistance
Handles frequent code explanation, generation and review requests while following project-specific instructions.
Visual Data Extraction
Extracts fields and findings from screenshots, charts and document pages for downstream review or indexing.
How to Use GPT-4.1 Mini via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)GPT-4.1 Mini Benchmarks
GPT-4.1 mini
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 16.3 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 18.5 |
| Artificial Analysis Math Index | Artificial Analysis math reasoning aggregate | 46.3 |
| Knowledge & Reasoning | ||
| MMLU-Pro | Advanced multi-task knowledge | 78.1% |
| GPQA | Advanced science problem solving | 66.4% |
| HLE | Broad expert-level exam set | 4.6% |
| Coding & Engineering | ||
| LiveCodeBench | Live coding problems | 48.3% |
| SciCode | Scientific coding challenges | 40.4% |
| Terminal-Bench Hard | Hard terminal task execution | 7.6% |
| Math | ||
| MATH-500 | Advanced math problem solving | 92.5% |
| AIME | Competition math problems | 43% |
| AIME 2025 | Competition math problems | 46.3% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 38.3% |
| AA-LCR | Long-context reasoning | 42.3% |
| τ²-Bench | Agent workflow tasks | 52.9% |
Metrics sourced from Artificial Analysis
Frequently asked questions about GPT-4.1 Mini
Understand what GPT-4.1 Mini is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
How should developers understand the role of GPT-4.1 Mini?+
GPT-4.1 Mini is a smaller, faster GPT-4.1-family model for efficient instruction following and tool-enabled applications. It has been retired from ChatGPT, while API availability may remain; check TokenHub’s current listing.
When does GPT-4.1 Mini deliver the most practical value?+
Best-fit scenarios include high-volume application requests, strict instruction following, and tool-enabled application workflows. Test representative inputs and define measurable acceptance criteria before production.
What are the most useful characteristics of GPT-4.1 Mini?+
Key strengths include fast response times, cost-efficient scaling, and strong handling of long context. This combination is especially useful for strict instruction following.
What are the practical limits of GPT-4.1 Mini?+
Consider another model when the task requires the provider’s strongest reasoning capability, quality matters more than speed or cost, or the workflow cannot include human review for important decisions. Verify important factual, legal, financial, medical, or operational outputs with qualified human review.
How should developers call GPT-4.1 Mini through TokenHub?+
In TokenHub, select the exact model identifier displayed for GPT-4.1 Mini, 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 Mini?
Use one API key to access GPT-4.1 Mini and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Reddit
YouTube