Model Selection Guide

Determine which large language model to use

Which Model Should I Use?

What to Consider

Choosing a model depends on the following:

1. Context Window: the context window refers to the number of tokens you can provide to a LLM. ~1 Token = ~4 characters

2. Task Complexity: more capable models are generally better suited for complex logic.

3. Web Access: whether the use case you're building require the model to have web access?

4. Cost: more capable models are generally more expensive - for example, o1 is more expensive than GPT-4o.

5. Speed: more capable models are generally slower to execute.

AirOps Popular LLMs

Model	Provider	Description	Context Window	Vision	JSON Mode	Web Access
GPT-5.2	OpenAI	Latest flagship with enhanced long-context reasoning	400K	✓	✓	✓
GPT-5.1	OpenAI	Flagship model with adaptive reasoning modes	400K	✓	✓	✓
GPT-5	OpenAI	Flagship model for complex tasks	400K	✓	✓	✓
GPT-4.1	OpenAI	For complex tasks, vision-capable	1M	✓	✓	-
GPT-4o Search Preview	OpenAI	Flagship model for online web research	128K	✓	✓	✓
O4 Mini	OpenAI	Fast multi-step reasoning for complex tasks	128K	-	✓	-
O3	OpenAI	Advanced reasoning for complex tasks	128K	-	✓	-
O3 Mini	OpenAI	Fast multi-step reasoning for complex tasks	128K	-	✓	-
Claude Opus 4.5	Anthropic	Most powerful Claude for complex multi-step tasks	200K	✓	-	-
Claude Opus 4.1	Anthropic	Powerful model for complex and writing tasks	200K	✓	-	-
Claude Sonnet 4.5	Anthropic	Best for agents and coding with web fetch capability	200K	✓	-	✓
Claude Sonnet 4	Anthropic	Hybrid reasoning: fast answers or deep thinking	200K	✓	-	-
Gemini 3 Pro	Google	Advanced multimodal reasoning for complex tasks	1M	✓	✓	✓
Gemini Flash 3	Google	Fast and intelligent model optimized for speed	1M	✓	✓	✓
Gemini 2.5 Pro	Google	Advanced reasoning for complex tasks	1M	✓	✓	✓
Gemini 2.5 Flash	Google	Fast and intelligent model for lightweight tasks	1M	✓	✓	✓
Perplexity Sonar	Perplexity	Balanced model for online web research	128K	-	✓	✓

Differences between “o-series” vs “GPT” models

GPT-5 Series: Built-In Reasoning

GPT-5 Models (5, 5.1, 5.2): OpenAI's model series that combines reasoning paradigm with traditional LLM capabilities. GPT-5.2 is the latest flagship with enhanced long-context reasoning and a knowledge cutoff of August 2025. GPT-5.1 introduced adaptive reasoning with "Instant" and "Thinking" modes. All GPT-5 models feature reasoning levels of minimal, low, medium, high that control how much reasoning the model performs.

O-series Models (o3, o4-mini): Pure Reasoning Specialists

Specialized exclusively for deep reasoning and step-by-step problem solving. These models excel at complex, multi-stage tasks requiring logical thinking and tool use. Choose these when maximum accuracy and reasoning depth are paramount. Features reasoning levels of low, medium, high for controlling reasoning token usage.

GPT Models (4.1, 4o): Traditional General-Purpose

Optimized for general-purpose tasks with excellent instruction following. GPT-4.1 excels with long contexts (1M tokens) while GPT-4o has variants for realtime speech, text-to-speech, and speech-to-text. GPT-4.1 also comes in mini and nano variants, while GPT-4o has a mini variant. These variants are cheaper and faster than their full-size counterparts. Strong in structured output generation.

Differences between Claude Models

Claude Opus 4.5: Most Powerful

Anthropic's flagship model for complex, multi-step workflows. Excels at long-form content, research tasks, and maintaining context across extended conversations. Choose Opus 4.5 when quality matters most.

Claude Sonnet 4.5: Best Value

Strong reasoning with built-in web fetch that can retrieve content from URLs in your prompts. Great balance of capability and cost for most marketing workflows.

Claude Sonnet 4 & Opus 4.1: Previous Generation

Solid models for straightforward tasks that don't require the latest capabilities.

Web Search Capabilities

Several models support web search, allowing them to access real-time information from the internet during generation:

OpenAI Models with Web Search: gpt-4o-mini, gpt-4o, gpt-4.1-mini, gpt-4.1, o4-mini, o3, GPT-5, GPT-5.1, and GPT-5.2 all support web search when enabled in the LLM step configuration.

Claude Sonnet 4.5 Web Fetch: Claude Sonnet 4.5 includes a unique web fetch capability that can grab and process the contents of URLs included in your prompts, making it ideal for workflows that need to analyze specific web pages.

Google Gemini: All Gemini models (2.5 Pro, 2.5 Flash, 3 Pro, Flash 3) support web access through Google Search grounding.

How much will it cost to run?

The cost to run a model depends on the number of input and output tokens.

Token Approximation

Input tokens: to approximate the total input tokens, copy and paste your system, user, and assistant prompts into the OpenAI tokenizer

Output tokens: to approximate the total output tokens, copy and paste your output into the OpenAI tokenizer

Cost Approximation

OpenAI: divide the input and output tokens by 1000; then multiply by their respective costs based on OpenAI pricing*

Anthropic: divide the input and output tokens by 1,000,000; then multiply by their respective costs based on Anthropic pricing*

*This is the cost if you bring your own API Key. If you choose to use AirOps hosted models, you will be charged tasks according to your usage.