Foundational Models
Clear Ideas integrates advanced language models (often called foundational models) from providers including OpenAI, Anthropic, Google, Cohere, XAI, and DeepSeek. This document describes how these models are used within the Clear Ideas platform, along with considerations for choosing the appropriate model.
Foundational models are AI models trained on large datasets that can generate text based on a user-provided prompt. They are designed to perform a wide range of tasks, such as:
- Factual Q&A
- Summarization
- Creative writing
- Technical/code-related queries
- Data analysis
Clear Ideas offers multiple models, each with different strengths, performance trade-offs, and associated costs.
Supported Models
Intelligent
Selects the most appropriate model for the task based on task type, reasoning level required, desired response length, target audience, creativity needs, and time sensitivity. Optimizes for cost efficiency when capabilities are equal.
GPT-4.1
GPT 4.1 is OpenAI's flagship model for complex tasks. It is well suited for problem solving across domains
GPT-4.1 mini
GPT 4.1 mini provides a balance between intelligence, speed, and cost that makes it an attractive model for many use cases.
GPT-4.1 nano
GPT-4.1 nano is the fastest, most cost-effective GPT 4.1 model.
OpenAI o3
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.
OpenAI o3 with High Reasoning Effort
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.
OpenAI o4 mini
o4-mini is OpenAI's latest small o-series model. It's optimized for fast, effective reasoning with exceptionally efficient performance in coding and visual tasks.
OpenAI o4 mini with High Reasoning Effort
o4-mini is OpenAI's latest small o-series model. It's optimized for fast, effective reasoning with exceptionally efficient performance in coding and visual tasks.
XAI Grok 3 Beta
XAI Grok 2. A versatile model with balanced capabilities across various task types. Suitable for interactive conversations and content creation with moderate reasoning requirements.
XAI Grok 3 Mini Beta
Grok 3 Mini is a lightweight, smaller thinking model. Unlike traditional models that generate answers immediately, Grok 3 Mini thinks before responding. It’s ideal for reasoning-heavy tasks that don’t demand extensive domain knowledge, and shines in math-specific and quantitative use cases, such as solving challenging puzzles or math problems.
XAI Grok 3 Mini Beta with High Reasoning Effort
Beta
Grok 3 Mini is a lightweight, smaller thinking model. Unlike traditional models that generate answers immediately, Grok 3 Mini thinks before responding. It’s ideal for reasoning-heavy tasks that don’t demand extensive domain knowledge, and shines in math-specific and quantitative use cases, such as solving challenging puzzles or math problems.
Gemini 2.0 Flash
Gemini 2.0 Flash is a robust and efficient AI model optimized for high-volume tasks requiring rapid responses. It provides excellent performance for real-time applications and is generally available
Gemini 2.5 Flash Preview
Beta
This is the latest, most efficient, and fastest Gemini model, designed for high-volume, low-latency applications. Currently in preview, it offers bleeding-edge speed for real-time tasks
Gemini 2.5 Pro Preview
Beta
This is the most capable and advanced Gemini model, built for complex reasoning, multimodal understanding, and massive context windows. Available as a preview, it represents the cutting edge of Google's AI power.
Claude 3.5 Haiku
Claude Haiku 3.5 is part of the Claude 3 family, typically designed for speed and efficiency in handling simpler tasks.
Claude 4.0 Sonnet
Claude Sonnet 4 is part of Anthropic's newest Claude 4 model family, designed as a smart and efficient solution for everyday tasks. It balances strong performance with accessibility, making it well-suited for general conversations, creative writing, analysis, and coding assistance.
Claude 4.0 Sonnet with Enhanced Reasoning
Claude Sonnet 4 is part of Anthropic's newest Claude 4 model family, designed as a smart and efficient solution for everyday tasks. It balances strong performance with accessibility, making it well-suited for general conversations, creative writing, analysis, and coding assistance.
Claude 4.0 Opus
Beta
Claude Opus 4 is the flagship model of the Claude 4 family, designed to handle the most complex tasks requiring advanced reasoning and problem-solving. It represents the highest tier of performance for sophisticated analytical work and technical assistance.
Claude 4.0 Opus with Enhanced Reasoning
Beta
Claude Opus 4 is the flagship model of the Claude 4 family, designed to handle the most complex tasks requiring advanced reasoning and problem-solving. It represents the highest tier of performance for sophisticated analytical work and technical assistance.
Command A
Cohere's Command A is a sophisticated large language model designed to assist users by providing thorough, accurate, and contextually relevant responses to a wide range of queries, while maintaining high efficiency in processing and delivering information, ensuring quick and reliable assistance.
Reasoning vs. Conversational Models
Clear Ideas offers models with a primary emphasis on reasoning or conversational capabilities. While there can be overlap, understanding each focus can help match the model to the task:
- Reasoning Models: Designed to handle more complex analytical tasks. These models are used when the goal is to perform in-depth analysis, solve technical problems, or produce detailed explanations. Reasoning-focused models often require more computational resources and can be more time-intensive, but they excel at:
- Complex problem-solving
- Logical or mathematical tasks
- Technical discussions and code assistance
- Data-driven analysis or research
- Conversational Models: Tailored primarily for natural, back-and-forth interactions. They are useful for human-like dialogue, making them well suited for:
- Q&A sessions or short clarifications
- Casual engagement or interactive scenarios
- Iterative brainstorming discussions
- High-level summaries or succinct explanations
When choosing between a reasoning or conversational model, consider the depth and complexity of your query. If the task involves sophisticated analysis, a reasoning model can be more appropriate. If you need an approachable dialogue or iterative exchange, a conversational model may be preferable.
Intelligent Model Selection
Clear Ideas provides an Intelligent auto-selector that evaluates multiple factors—such as task complexity, desired detail level, audience type, and cost constraints—to pick the most suitable model. If multiple models appear equally suitable, the selection process favors the lower-cost option. This approach reduces the need for manual model comparison.
Model Selection Considerations
Task Complexity
- Lower complexity (summarization, short Q&A):
- Higher complexity (in-depth analysis, technical tasks):
Response Length
- Brief responses
- Extended output
Audience
- General audience
- Expert audience
Time Sensitivity
- High time sensitivity
- Lower time sensitivity
Creativity
- Lower creativity needed
- Higher creativity needed