gpt-4o-mini-search-preview

completions

byopenai

gpt-4o-mini-search-preview

completions

Published by: openaiProvider:

openai

GPT-4o mini Search Preview is a specialized model trained to understand and execute web search queries with the Chat Completions API.

Released

Jul 18, 2024

Knowledge

Oct 1, 2023

License

Proprietary

Context

128K

Input

$0.15 / 1M tokens

Output

$0.6 / 1M tokens

Accepts: text

Returns: text

Released Jul 18, 2024Knowledge Cutoff: Oct 1, 2023License: Proprietary

Context: 128K Input: $0.15 / 1M tokensOutput: $0.6 / 1M tokensAccepts: textReturns: text

Access gpt-4o-mini-search-preview through LangDB AI Gateway

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Benchmark Results for gpt-4o-mini-search-preview

Category Performance Scores:

Vision: Score 59.40 (Top 81% - Rank #282)
Science: Score 43.69 (Top 87% - Rank #303)
Writing: Score 40.20 (Top 73% - Rank #255)

Overall Performance: 47.76363636363637 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
DROP	79.70	Top 53%	General Knowledge
GPQA	40.20	Top 87%	STEM (Physics, Chemistry, Biology)
MMMU	59.40	Top 81%	General Knowledge

GPQA Score: 40.20 - Graduate-level reasoning benchmark

Model Comparison:

Provider: openai

Model Type: completions

Context Size: 128000 tokens

Comparing against 348 models in the database

Category Scores

Benchmark Tests

View Other Benchmarks

DROP

79.7

General Knowledge

GPQA

40.2

STEM (Physics, Chemistry, Biology)

MMMU

59.4

General Knowledge

Metric	DROP	GPQA	MMMU
Score	79.7	40.2	59.4

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Code Examples

Integration samples and API usage

Code Samples for gpt-4o-mini-search-preview

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="gpt-4o-mini-search-preview",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "gpt-4o-mini-search-preview",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini-search-preview",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: gpt-4o-mini-search-preview

Provider: openai

API Endpoint: $https://api.langdb.ai

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