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Model details

GPT-4.1-mini

GPT-4.1-mini is positioned as a cost-performance option within the GPT-4.1 family, designed to deliver GPT-4o-class intelligence at reduced cost with significantly lower latency. It combines a million-token context window with strong performance across instruction following, reasoning, and knowledge tasks. The model demonstrates particular strength in coding scenarios and vision understanding, making it well-suited for interactive applications where both capability and efficiency matter.

The model shows solid benchmark performance across multiple domains—achieving notable scores on coding tasks like SWE-Bench Verified, graduate-level reasoning as measured by GPQA Diamond, and broad knowledge understanding through MMLU Pro. Its throughput capabilities and competitive pricing structure position it as a practical choice for high-volume production environments. The model handles file inputs, tool calling, and vision tasks, which suggests it's engineered for complex workflows rather than simple text generation alone. This combination of capability breadth and efficiency makes it a strong candidate for interactive applications where both performance and cost matter.

Poeopenai/gpt-4.1-minigpt-mini

Quick Info

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Provider
Poe
Model key
openai/gpt-4.1-mini
Release date
Apr 15, 2025
Last updated
Apr 15, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.36
Output token cost
$1.40

Limits

Output tokens
32,768 tokens
Context window
1,047,576 tokens

Transparent token rates

Compare GPT-4.1-mini pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GPT-4.1-mini

SAP AI Core

CoverageBenchmark

BenchLM's catalog page for GPT-4.1 mini lists an established release date of April 14, 2025, classifies the model as proprietary and non-reasoning, and records a 1 million-token context window. The page reports a composite capability score of 44.4 out of 100, ranking the model 174 of 229 in the tracked catalog, with it On cost and throughput, BenchLM records API pricing at $0.40 per million input tokens and $1.60 per million output tokens, a measured speed of roughly 80 tokens per second, and a first-token latency near 0.76 seconds. The page notes data as of September 1, 2026 and presents percentile breakdowns across capability axes,

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