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OpenAI: o1-mini (2024-09-12)

OpenAI's o1-mini is a cutting-edge AI model designed for STEM tasks. It excels in math, science, and programming. This model is known for its ability to think deeply before responding. It consistently achieves high accuracy on benchmarks in physics, chemistry, and biology. Users can access o1-mini through an API, making it easy to integrate into various applications.

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "openai/o1-mini-2024-09-12",
    messages: [
      {
        "role": "user",
        "content": "Write a blog about cat."
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()

OpenAI: o1-mini (2024-09-12)

Context128000
Input$3 / M
Output$12 / M

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Description

OpenAI launched the o1-mini model on September 12, 2024. This model is a strong tool for reasoning in STEM areas. It performs well in math, science, and programming tasks. The o1-mini scored 70% on the American Invitational Mathematics Examination (AIME). This score places it among the top 500 high school students in the U.S. The model focuses on STEM-related training. This approach boosts its skills in logical reasoning and problem-solving. In coding contests like Codeforces, o1-mini earned an Elo rating of 1650. This rating puts it in the 86th percentile of programmers, showing its strong coding skills. The o1-mini can handle a context window of 128,000 tokens. This feature helps it process large amounts of information quickly. It also shows high accuracy in physics, chemistry, and biology benchmarks. The model is designed for speed and cost efficiency, making it useful in education and research. Despite its small size, o1-mini has excellent reasoning skills. It often outperforms larger models in specific areas. This makes it especially helpful for developers and researchers who need fast and precise answers. Overall, the OpenAI o1-mini model marks a big step forward in AI technology. It is a practical tool for users across many fields. Use our AIAPILAB service to integrate this model for better pricing options.

Model API Use Case

The o1-mini API is great for STEM uses. It works well for educational tools and coding platforms. For example, it scored 70% on the American Invitational Mathematics Examination (AIME). This score puts it among the top 500 high school students in the U.S. Such performance shows it can help students learn tough math concepts. In coding, o1-mini achieved an Elo rating of 1650 on Codeforces. This rating places it in the 86th percentile. Developers can use this API for tasks like code generation and debugging. This greatly boosts productivity. Additionally, o1-mini is affordable at $3 per million input tokens. Output tokens cost $12 per million, making it easy for startups and schools to use. By using this API, organizations can create smart tutoring systems. They can also automate software development and improve scientific research. The o1-mini API is a strong tool for those wanting advanced AI without spending too much.

Model Review

Pros

1. o1-mini excels in STEM tasks, delivering precise solutions rapidly. 2. It achieves high scores in math exams, demonstrating advanced reasoning skills. 3. The model processes large contexts, enhancing its understanding of complex queries. 4. It generates efficient code, aiding developers in software tasks. 5. o1-mini outshines larger models in specific areas, making it a powerful tool for research.

Cons

1. The o1-mini struggles with non-STEM topics, yielding weak performance in history and literature. 2. Response times may lag due to its in-depth reasoning process, delaying answers in urgent tasks. 3. Limited multimodal capabilities hinder its use, as it cannot handle images or real-time data.

Comparison

Feature/Aspecto1-previewGPT-4 (General Purpose)OpenAI: o1-mini (2024-09-12)
SpeedSlower due to deep reasoningModerate response timesFast response times (3-5x faster than GPT-4)
SpecializationAdvanced reasoningGeneral-purpose capabilitiesOptimized for STEM tasks
Knowledge ScopeBalanced knowledge, excels in reasoningBroad knowledge across domainsStrong in STEM, limited in non-STEM
Performance in STEMSuperior in reasoning tasksGood general performanceHigh accuracy in math and science benchmarks
Reasoning MethodologyEnhanced reasoning capabilitiesPredictive text generationChain-of-thought reasoning

API

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "openai/o1-mini-2024-09-12",
    messages: [
      {
        "role": "user",
        "content": "Write a blog about cat."
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()
from openai import OpenAI

client = OpenAI(
  base_url="https://api.aiapilab.com/v1",
  api_key="$AIAPILAB_API_KEY",
)

completion = client.chat.completions.create(
  model="openai/o1-mini-2024-09-12",
  messages=[
    {
      "role": "user",
      "content": "Write a blog about cat."
    }
  ]
)
print(completion.choices[0].message.content)

FAQ

Q1: What tasks does the o1-mini model excel at? A1: The o1-mini model excels in math, science, and programming tasks. Q2: How does o1-mini handle reasoning? A2: o1-mini utilizes a chain-of-thought process for deeper reasoning. Q3: Can o1-mini process large amounts of data? A3: Yes, o1-mini supports a context window of 128,000 tokens. Q4: What is the main advantage of using o1-mini? A4: o1-mini offers fast responses while maintaining high accuracy. Q5: Is o1-mini suitable for production use? A5: No, o1-mini is currently experimental and not for production.

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