Sold by: Articul8 AIÂ
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LLM-IQ Agent API enables fast, code-free evaluation and comparison of top large language models like GPT-4, Claude 3, Gemini, Mistral, and Cohere. Designed for enterprise teams, it supports natural language queries to assess model performance across 25+ real-world use cases including reasoning, summarization, extraction, and query generation without the need for prompt engineering, dataset creation, or framework setup. With built-in performance benchmarking and domain-specific metrics, the API streamlines model selection and validation for AI, procurement, and compliance workflows.
Overview
The LLM IQ Agent API is a plug and play evaluation platform designed for enterprises seeking to benchmark and compare large language models (LLMs) such as GPT-4, Claude 3, Gemini, Mistral, and Cohere without the overhead of prompt engineering, dataset curation, or framework configuration.
Using natural language queries, teams can instantly access comprehensive benchmarking results across 25+ enterprise-grade evaluation domains, including reasoning, summarization, extraction, and query generation. The API supports questions like What is the best model for financial document summarization? or Compare Claude 3 and GPT-4 on reasoning tasks. Behind the scenes, it runs precision-tuned tests using multiple prompt variations and decoding strategies to simulate realistic workflows.
With actionable insights delivered through a professional-grade API, LLM-IQ Agent API enables intelligent decision-making at every stage of the GenAI lifecycle. Development teams can embed the API directly into inference workflows to power real-time model selection and dynamic prompt routing, automatically choosing the best-fit model for each user query. Procurement and vendor management functions gain standardized metrics for evaluating LLM providers, while engineering teams can offload the burden of framework development. For regulated industries, the API offers audit-ready evaluations aligned to compliance standards and domain-specific requirements. With LLM-IQ, enterprises gain a trusted layer of evaluation and transparency to support retrieval-augmented generation (RAG), multi-agent orchestration, and large-scale model deployment strategies.
Highlights
- Natural language-driven LLM evaluation API benchmark GPT-4, Claude 3, Gemini, and more with no setup required
- Covers 25+ enterprise use cases such as reasoning, summarization, extraction, query generation, and more
- Objective, real-time model benchmarking powered by proprietary prompt engineering and decoding strategies
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Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/request |
|---|---|---|
Successful API Requests | Number of successful API requests completed | $0.06 |
Vendor refund policy
Articul8 charges only for successful API requests. Failed or incomplete requests are excluded from billing. Refunds or credits may be issued if a failed request was misclassified or usage was misattributed. Requests must be submitted within 15 days with relevant logs. Refunds are typically issued as credits; monetary refunds are only provided in cases of billing errors.
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- Amazon Bedrock AgentCore - Preview
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API-Based Agents and Tools integrate through standard web protocols. Your applications can make API calls to access agent capabilities and receive responses.
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Usage instructions
API
LLM-IQ Agent
The LLM-IQ Agent is an intelligent assistant for selecting the optimal AI model for your specific needs. By analyzing comprehensive benchmark data and utilizing advanced querying capabilities, this agent delivers personalized model recommendations based on natural language queries.
Whether you're comparing model performance, seeking the best option for specific tasks, or simply exploring available models, LLM-IQ Agent provides data-driven insights to inform your decision-making process.
How It Works
The LLM-IQ Agent operates using a comprehensive dataset of model evaluations containing information about various models, their parameters, evaluation methods, and performance results. This data powers several specialized tools that the agent employs to answer your queries, including:
- Data extraction tools for retrieving specific model information
- Filtering mechanisms to narrow down results based on criteria
- Aggregation tools for creating sorted summaries and rankings
- Dataset information tools for providing context about available data
When you submit a query, the LLM-IQ agent analyzes it, selects the appropriate tools, processes the benchmark data, and delivers relevant recommendations.
Key Benefits:
- Simplified model selection through natural language queries
- Integration into inference pipeline for intelligent prompt routing
- Data-driven recommendations based on comprehensive benchmarks
- Easy comparison of model performance across different tasks
- Time-saving insights that eliminate manual research
Example Queries
The LLM-IQ Agent can answer a wide range of questions about current open- and closed-source models.
Here are some example queries you can try :
- "Which models can I evaluate right now?"
- "Which model excels at performing grounded chat?"
- "How do GPT-4 and Claude 3 compare for financial documents?"
- "What evaluation categories do you cover?"
- "What is the best model for generating queries from a context?"
- “I want to summarize the key insights on the Morocco economy. What model should we use?”
API Usage
Ask the LLM-IQ Agent your questions as a simple string in the request body of your POST request.
For detailed instructions visit https://agents.articul8.aiÂ
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