OpenAI

OpenAI provides a comprehensive suite of language models optimized for different use cases, from high-intelligence reasoning to cost-efficient production tasks. Tambo supports the full range of OpenAI models, including the latest GPT-5 series with advanced reasoning capabilities.

Supported Models

Tambo supports 12 OpenAI models organized into five families:

GPT-5 Family

The latest generation of OpenAI models with advanced reasoning capabilities and massive context windows.

gpt-5

Status: Tested API Name: gpt-5-2025-08-07 Context Window: 400,000 tokens Provider Docs: OpenAI GPT-5

The flagship GPT-5 model, best for coding and agentic tasks across domains. Supports reasoning parameters for exposing internal thought processes.

Best for:

• Complex coding tasks and refactoring
• Agentic workflows requiring multi-step reasoning
• Tasks requiring deep analysis and problem-solving
• Applications where showing reasoning builds trust

Notes: The most powerful model for reasoning-intensive tasks. Use reasoningEffort and reasoningSummary parameters to control thinking behavior.

gpt-5-mini

Status: Tested API Name: gpt-5-mini-2025-08-07 Context Window: 400,000 tokens Provider Docs: OpenAI GPT-5 Mini

A faster, more cost-efficient version of GPT-5 for well-defined tasks.

Best for:

• Production applications requiring balance of intelligence and cost
• Well-scoped tasks with clear requirements
• High-volume reasoning workloads
• Applications where latency matters

Notes: Maintains GPT-5's reasoning capabilities while optimizing for speed and cost. Ideal for production deployments.

gpt-5-nano

Status: Tested API Name: gpt-5-nano-2025-08-07 Context Window: 400,000 tokens Provider Docs: OpenAI GPT-5 Nano

The fastest, most cost-efficient version of GPT-5.

Best for:

• High-volume applications requiring reasoning at scale
• Simple reasoning tasks
• Latency-sensitive applications
• Cost-optimized production deployments

Notes: Smallest GPT-5 variant, optimized for efficiency while retaining reasoning capabilities.

gpt-5.1 Thinking

Status: Tested API Name: gpt-5.1 Context Window: 400,000 tokens Provider Docs: OpenAI Latest Model

GPT-5.1 Thinking with adaptive reasoning. Dynamically varies thinking time based on task complexity for better token efficiency.

Best for:

• Tasks with variable complexity
• Applications requiring intelligent cost optimization
• Complex problem-solving with automatic effort adjustment
• Production systems handling diverse query types

Notes: Released November 2025. Adaptive reasoning automatically adjusts thinking time, optimizing cost without sacrificing quality on complex tasks.

gpt-5.1 Instant

Status: Tested API Name: gpt-5.1-chat-latest Context Window: 400,000 tokens Provider Docs: OpenAI Latest Model

GPT-5.1 Instant - warmer, more conversational model with adaptive reasoning. Defaults to 'none' reasoning effort for latency-sensitive workloads.

Best for:

• Conversational applications requiring natural responses
• Latency-sensitive chat interfaces
• Applications balancing warmth and intelligence
• Real-time interactions with optional reasoning

Notes: Released November 2025. Latest conversational variant with improved responsiveness. Defaults to minimal reasoning for speed but can be configured for deeper thinking when needed.

GPT-4.1 Family

High-intelligence models excelling at function calling and instruction following with massive context windows.

gpt-4.1

Status: Tested (Default Model) API Name: gpt-4.1-2025-04-14 Context Window: 1,047,576 tokens Provider Docs: OpenAI GPT-4.1

The default model for Tambo projects. Excels at function calling and instruction following.

Best for:

• Function calling and tool use
• Following complex instructions precisely
• General-purpose applications
• Large context requirements (1M+ tokens)

Notes: This is Tambo's default model, balancing intelligence, reliability, and cost. Ideal for most production applications.

gpt-4.1-mini

Status: Tested API Name: gpt-4.1-mini-2025-04-14 Context Window: 1,047,576 tokens Provider Docs: OpenAI GPT-4.1 Mini

Balanced for intelligence, speed, and cost.

Best for:

• Production applications requiring cost efficiency
• High-volume workloads
• Applications balancing quality and performance
• Large context with cost constraints

Notes: Offers excellent value proposition with maintained quality at reduced cost.

gpt-4.1-nano

Status: Untested API Name: gpt-4.1-nano-2025-04-14 Context Window: 1,047,576 tokens Provider Docs: OpenAI GPT-4.1 Nano

Fastest, most cost-efficient version of GPT-4.1.

Best for:

• Maximum throughput applications
• Simple, well-defined tasks
• Cost-critical deployments
• High-volume production systems

Notes: Released November 2025. The fastest GPT-4.1 variant optimized for efficiency. Not yet validated on common Tambo tasks - use with caution and test in your specific context.

o3 Family

Specialized reasoning model for complex problem-solving.

o3

Status: Tested API Name: o3-2025-04-16 Context Window: 200,000 tokens Provider Docs: OpenAI o3

The most powerful reasoning model available.

Best for:

• Mathematical proofs and calculations
• Complex code review and debugging
• Strategic planning requiring deep analysis
• Research and analysis tasks
• Any task where showing reasoning is critical

Notes: Dedicated reasoning model with the most powerful thinking capabilities. Higher latency and cost but unmatched reasoning depth.

GPT-4o Family

Versatile multimodal models with text and image input support.

gpt-4o

Status: Tested API Name: gpt-4o-2024-11-20 Context Window: 128,000 tokens Provider Docs: OpenAI GPT-4o

Versatile and high-intelligence model with text and image input support. Best for most tasks, combining strong reasoning, creativity, and multimodal understanding.

Best for:

• Multimodal applications (text + images)
• Creative tasks requiring nuanced understanding
• General-purpose applications requiring versatility
• Tasks requiring both analysis and generation

Notes: Excellent all-around model with multimodal capabilities. Strong choice when you need both text and image understanding.

gpt-4o-mini

Status: Tested API Name: gpt-4o-mini-2024-07-18 Context Window: 128,000 tokens Provider Docs: OpenAI GPT-4o Mini

Fast, affordable model ideal for focused tasks and fine-tuning. Supports text and image inputs, with low cost and latency for efficient performance.

Best for:

• Cost-sensitive multimodal applications
• Fine-tuning for specific use cases
• High-volume image analysis
• Production deployments prioritizing efficiency

Notes: Most efficient multimodal option with excellent performance-to-cost ratio.

GPT-4 Turbo Family

Previous generation high-intelligence model, still powerful but superseded by newer families.

gpt-4-turbo

Status: Tested API Name: gpt-4-turbo-2024-04-09 Context Window: 128,000 tokens Provider Docs: OpenAI GPT-4 Turbo

High-intelligence model that's cheaper and faster than GPT-4. Still powerful, but we recommend using GPT-4o for most tasks.

Best for:

• Legacy applications requiring GPT-4 Turbo specifically
• Cost-conscious deployments not yet migrated to newer models

Notes: While still capable, GPT-4o and GPT-4.1 families offer better performance and features for most use cases.

Provider-Specific Parameters

OpenAI reasoning models support specialized parameters to control their thinking behavior.

Reasoning Parameters

Configure reasoning capabilities through your project's LLM provider settings in the dashboard.

reasoningEffort

Type: string Values: "minimal", "low", "medium", "high" Description: Controls the intensity of the model's reasoning process. Only effective when reasoningSummary is also set.

• "minimal" - Quick reasoning with minimal thinking time
• "low" - Light reasoning for simpler tasks (faster, cheaper)
• "medium" - Balanced reasoning for most use cases (recommended)
• "high" - Deep reasoning for complex problems (slower, more expensive)

reasoningSummary

Type: string Values: "auto", "detailed" Description: Enables reasoning token output, allowing you to see the model's internal thought process.

• "auto" - Automatically determines appropriate reasoning detail level
• "detailed" - Provides more comprehensive reasoning output

Example Configuration:

In your Tambo Cloud dashboard under Settings → LLM Providers → Custom LLM Parameters:

reasoningEffort: "medium"
reasoningSummary: "auto"

Supported Reasoning Models

Reasoning parameters are available for the following OpenAI models:

• GPT-5 (gpt-5-2025-08-07)
• GPT-5 Mini (gpt-5-mini-2025-08-07)
• GPT-5 Nano (gpt-5-nano-2025-08-07)
• GPT-5.1 (gpt-5.1)
• GPT-5.1 Chat Latest (gpt-5.1-chat-latest)
• o3 (o3-2025-04-16)

Configuration

Setting Up OpenAI in Tambo

1. Navigate to your project in the Tambo Cloud dashboard
2. Go to Settings → LLM Providers
3. Select OpenAI as your provider
4. Choose your desired model from the dropdown
5. Configure any provider-specific parameters (reasoning, temperature, etc.)
6. Click Save

Dashboard Features

When you select an OpenAI reasoning model, the dashboard automatically suggests relevant parameters:

• reasoningEffort - Suggested for all reasoning models
• reasoningSummary - Suggested for all reasoning models

Simply click the suggested parameter to add it to your configuration, set the desired value, and save.

Best Practices

Model Selection:

• Use gpt-4.1 for most production applications (default)
• Use gpt-5 family when reasoning capabilities are critical
• Use gpt-4o for multimodal applications
• Use mini/nano variants for cost-optimized deployments
• Use o3 for maximum reasoning depth

Reasoning Configuration:

• Start with reasoningEffort: "medium" for balanced performance
• Set reasoningSummary: "auto" to enable reasoning display
• Increase effort for complex tasks, decrease for simple queries
• Monitor token usage as reasoning consumes additional tokens

Production Considerations:

• Test untested models thoroughly before production deployment
• Monitor costs with reasoning parameters enabled
• Use separate projects for different reasoning requirements
• Consider using non-reasoning models for high-volume simple tasks

See Also

• Labels - Understanding model status labels and observed behaviors
• Custom LLM Parameters - Configuring temperature, max tokens, and other parameters
• Reasoning Models - Deep dive into reasoning capabilities for OpenAI and Gemini models