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LLM Models
Agent.ai provides a number of LLM models that are available for use.
LLM Models
Selecting the right Large Language Model (LLM) for your application is a critical decision that impacts performance, cost, and user experience. This guide provides a comprehensive comparison of leading LLMs to help you make an informed choice based on your specific requirements.How to Select the Right LLM
When choosing an LLM, consider these key factors:- Task Complexity: For complex reasoning, research, or creative tasks, prioritize models with high accuracy scores (8-10), even if they’re slower or more expensive. For simpler, routine tasks, models with moderate accuracy (6-8) but higher speed may be sufficient.
- Response Time Requirements: If your application needs real-time interactions, prioritize models with speed ratings of 8-10. Customer-facing applications generally benefit from faster models to maintain engagement.
- Context Needs: If your application processes long documents or requires maintaining extended conversations, select models with context window ratings of 8 or higher. Some specialized tasks might work fine with smaller context windows.
- Budget Constraints: Cost varies dramatically across models. Free and low-cost options (0-2 on our relative scale) can be excellent for startups or high-volume applications, while premium models (5+) might be justified for mission-critical enterprise applications where accuracy is paramount.
- Specific Capabilities: Some models excel at particular tasks like code generation, multimodal understanding, or multilingual support. Review the use cases to find models that specialize in your specific needs.
Vendor Overview
OpenAI: Offers the most diverse range of models with industry-leading capabilities, though often at premium price points, with particular strengths in reasoning and multimodal applications. Anthropic (Claude): Focuses on highly reliable, safety-aligned models with exceptional context length capabilities, making them ideal for document analysis and complex reasoning tasks. Google: Provides models with impressive context windows and competitive pricing, with the Gemini series offering particularly strong performance in creative and analytical tasks. Perplexity: Specializes in research-oriented models with unique web search integration, offering free access to powerful research capabilities and real-time information. Other Vendors: Offer open-source and specialized models that provide strong performance at minimal or no cost, making advanced AI accessible for deployment in resource-constrained environments.OpenAI Models
| Model | Speed | Accuracy | Context Window | Relative Cost | Use Cases |
|---|---|---|---|---|---|
| GPT-4o | 9 | 9 | 9 | 3 | • Multimodal assistant for text, audio, and images • Complex reasoning and coding tasks • Cost-sensitive deployments |
| GPT-4o-Mini | 10 | 8 | 9 | 1 | • Real-time chatbots and high-volume applications • Long-context processing • General AI assistant tasks where affordability and speed are prioritized |
| GPT-4 Vision | 5 | 9 | 5 | 5 | • Image analysis and description • High-accuracy general assistant tasks • Creative and technical writing with visual context |
| o1 | 6 | 10 | 9 | 4 | • Tackling highly complex problems in science, math, and coding • Advanced strategy or research planning • Scenarios accepting high latency/cost for superior accuracy |
| o1 Mini | 8 | 8 | 9 | 1 | • Coding assistants and developer tools • Reasoning tasks that need efficiency over broad knowledge • Applications requiring moderate reasoning but faster responses |
| o3 Mini | 9 | 9 | 9 | 1 | • General-purpose chatbot for coding, math, science • Developer integrations • High-throughput AI services |
| GPT-4.5 | 5 | 10 | 9 | 10 | • Mission-critical AI tasks requiring top-tier intelligence • Highly complex problem solving or content generation • Multi-modal and extended context applications |
Anthropic (Claude) Models
| Model | Speed | Accuracy | Context Window | Relative Cost | Use Cases |
|---|---|---|---|---|---|
| Claude 3.7 Sonnet | 8 | 9 | 9 | 2 | • Advanced coding and debugging assistant • Complex analytical tasks • Fast turnaround on detailed answers |
| Claude 3.5 Sonnet | 7 | 8 | 9 | 2 | • General-purpose AI assistant for long documents • Coding help and Q&A • Everyday reasoning tasks with high reliability and alignment |
| Claude 3.5 Sonnet Multi-Modal | 7 | 8 | 9 | 2 | • Image understanding in French or English • Multi-modal customer support • Research assistants combining text and visual data |
| Claude Opus | 6 | 7 | 9 | 9 | • High-precision analysis for complex queries • Long-form content summarization or generation • Enterprise scenarios requiring strict reliability |
Google Models
| Model | Speed | Accuracy | Context Window | Relative Cost | Use Cases |
|---|---|---|---|---|---|
| Gemini 2.0 Pro | 7 | 10 | 8 | 5 | • Expert code generation and debugging • Complex prompt handling and multi-step reasoning • Cutting-edge research applications requiring maximum accuracy |
| Gemini 2.0 Flash | 9 | 9 | 10 | 1 | • Interactive agents and chatbots • General enterprise AI tasks at scale • Large-context processing up to ~1M tokens |
| Gemini 2.0 Flash Thinking Mode | 8 | 9 | 10 | 2 | • Improved reasoning in QA and problem-solving • Explainable AI scenarios • Tasks requiring a balance of speed and reasoning accuracy |
| Gemini 1.5 Pro | 7 | 9 | 10 | 1 | • Sophisticated coding and mathematical problem solving • Processing extremely large contexts • Use cases tolerating higher cost/latency for higher quality |
| Gemini 1.5 Flash | 9 | 7 | 10 | 1 | • Real-time assistants and chat services • Handling lengthy inputs • General tasks requiring decent reasoning at minimal cost |
| Gemma 7B It | 10 | 6 | 4 | 1 | • Italian-language chatbot and content generation • Lightweight reasoning and coding help • On-device or private deployments |
| Gemma2 9B It | 9 | 7 | 5 | 1 | • Multilingual assistant • Developer assistant on a budget • Text analysis with moderate complexity |
Perplexity Models
| Model | Speed | Accuracy | Context Window | Relative Cost | Use Cases |
|---|---|---|---|---|---|
| Perplexity | 10 | 7 | 4 | 1 | • Quick factual Q&A with web citations • Fast information lookups • General knowledge queries for free |
| Perplexity Deep Research | 3 | 9 | 10 | 1 | • In-depth research reports on any topic • Complex multi-hop questions requiring reasoning and evidence • Scholarly or investigative writing assistance |
Open Source Models
| Model | Speed | Accuracy | Context Window | Relative Cost | Use Cases |
|---|---|---|---|---|---|
| DeepSeek R1 | 7 | 9 | 9 | 1 | • Advanced reasoning engine for math and code • Integrating into Retrieval-Augmented Generation pipelines • Open-source AI deployments needing strong reasoning |
| Llama 3.3 70B | 8 | 9 | 9 | 1 | • Versatile technical and creative assistant • High-quality AI for smaller setups • Resource-efficient deployment |
| Mixtral 8×7B 32K | 9 | 8 | 8 | 1 | • General-purpose open-source chatbot • Long document analysis and retrieval QA • Scenarios needing both efficiency and quality on modest hardware |