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Favicon for openai

OpenAI: GPT-4o-mini

openai/gpt-4o-mini

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GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.

As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

GPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences common leaderboardsOpens in new tab.

Check out the launch announcementOpens in new tab to learn more.

#multimodal

Modalities
In / Out Price
$0.15 / $0.60per 1M
Context
128K
Released
Jul 18, 2024
Knowledge Cutoff
Oct 2023
Compare
ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for OpenAI: GPT-4o-mini (Artificial Analysis)
SourceBenchmarkScore
Artificial AnalysisGPT-4o mini Intelligence Index6.7
Artificial AnalysisGPT-4o mini Coding Index11.4
Artificial AnalysisGPT-4o mini Math Index14.7
Artificial AnalysisGPT-4o mini GPQA Diamond42.6%
Artificial AnalysisGPT-4o mini HLE4.2%
Artificial AnalysisGPT-4o mini IFBench31.0%
Artificial AnalysisGPT-4o mini τ-Bench Banking2.9%
Artificial AnalysisGPT-4o mini GDPval-AA0.0%
Artificial AnalysisGPT-4o mini LiveCodeBench23.4%
Artificial AnalysisGPT-4o mini Terminal-Bench 2.15.6%
Artificial AnalysisGPT-4o mini MMLU-Pro64.8%
Artificial AnalysisGPT-4o mini AIME 202514.7%
Artificial AnalysisGPT-4o mini AIME11.7%
Artificial AnalysisGPT-4o mini MATH-50078.9%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Available through EU in-region routing

OpenAI: GPT-4o-mini is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).

Providers in Europe
Azure
Prices in Europe
  • Azure: $0.165/M tokens input, $0.66/M tokens output
Base URL
https://eu.openrouter.ai/api/v1
Plan
Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing

Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs

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AutoExacto benchmarks
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Frequently asked questions

GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

GPT-4o-mini costs $0.15/M input tokens and $0.60/M output tokens, with separate rates for Cache Read at $0.075/M tokens.

GPT-4o-mini has a 128,000 token context window. It supports up to 16,384 completion tokens.

Yes. GPT-4o-mini accepts tools and tool_choice for function calling on 1 of the 2 providers serving it, and requests that send tools are routed to those providers. It also supports structured outputs via a JSON schema in response_format.

GPT-4o-mini accepts text, images, and files such as PDFs as input and returns text.

GPT-4o-mini is served by 2 providers on OpenRouter: Azure and OpenAI. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

GPT-4o-mini was released on July 18, 2024. Its knowledge cutoff is October 31, 2023.

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GPT-6 Luna Decisions is GPT-6 Luna served through OpenAI's Decisions API. Instead of generating text, it reads the content passed as state (text, JSON, or images) and returns typed, probabilistic answers to named questions in a single request: the probability of yes for a yes/no question (noul), a probability for every option plus the most likely one (choice), or a probability for every level of an ordered rubric plus the expected score (score).

It is built for classification, routing, moderation, and rubric grading where application code thresholds the returned numbers rather than parsing a chat reply. A request can carry up to 200 questions about the same content.

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GPT-6.1 Sol Pro is the same underlying model as GPT-6.1 Sol, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6.1 Sol

GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.

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GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Luna and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Luna instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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