Selecting an LLM

Choose the right AI model for your Playlab project

Updated

New: Claude 5.5 Opus, Claude 5.5 Sonnet, and Claude 5.5 Haiku are now available in Playlab. GPT 6.1 Sol and GPT 6 Luna are now available as well.

New Models Added Regularly! We’re constantly adding and updating models to give Playlabbers access to the latest AI capabilities. Our goal is to provide more open weight models and eventually open source models to give you maximum flexibility and control over your applications.

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What is this feature?

You can now build on top of even more LLMs in Playlab! There are now more than a dozen available AI models for you to build your Playlab apps on top of. We will try our best to always provide the latest models for you to build on top of.

Changing the LLM may impact the performance of your app.

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Rationale for the feature

This feature allows Playlab users to experiment with and leverage the unique strengths of various AI models from different providers all within Playlab.

As you build, you might find that certain models perform better at different tasks. This will allow Playlab users to select the model that fits their needs better. The more available models, the more likely you are to find one that meets your needs. We believe that Playlabbers should have access to frontier models as we build in community.

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Understanding Model Types

Before selecting a model, it’s helpful to understand the different categories of AI models available:

Frontier Models	Open Weight Models	Open Source Models
Cutting-edge, proprietary models developed by major AI companies	Models with publicly available parameters (weights) that can be downloaded and run independently	Fully open models where both weights and training code are publicly available
Typically offer the most advanced capabilities and are continuously updated with the latest research breakthroughs	While training code may not be available, you have more control over deployment and customization	Offer maximum transparency and customization potential

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How do I access these models?

1. Click the LLM selector

   On the top left click the LLM. (New apps start on Claude 5.5 Sonnet)
2. Choose your model

   From the menu, select which LLM you want to build on top of. Each model shows its knowledge cutoff date so you can pick based on how current you need the model to be. You can read more about available models below in greater detail.

   
3. Build and Test

   See how the model you chose impacts your app. Continue trying out different models to find the “best” fit for your app.

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Compare models

Use these resources as a starting point, then test models on your own app’s tasks.

• Arena leaderboard: Measures AI in real-world use, with leaderboards powered by real people doing real work on Arena around the globe.
• Artificial Analysis: Independent analysis of AI to help you compare models.

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Which models should I use?

Now that you know how to select models, here are some strengths and tradeoffs of each:

Claude 5.5 Opus (Anthropic)

For complex projects, agents, and coding. Creates the best looking artifacts.

Knowledge Cutoff: Jun 2026

Claude 5.5 Sonnet (Anthropic)

The default model for new apps. A cost-efficient choice for everyday tasks and writing. Creates the best looking artifacts.

Knowledge Cutoff: Jun 2026

Claude 5.5 Haiku (Anthropic)

The fastest, lowest-cost option in the Claude 5.5 family, suited to high-volume tasks.

Knowledge Cutoff: Jun 2026

GPT 6.1 Sol (OpenAI)

For complex coding, computer use, and professional work.

Knowledge Cutoff: Apr 30, 2026

GPT 6 Luna (OpenAI)

OpenAI’s most efficient model for focused, high-volume tasks.

Knowledge Cutoff: May 18, 2026

Claude Opus 4.6 (Anthropic)

Frontier Model Non-Reasoning

Complex analysis, multi-step tasks, and advanced math and coding.

Knowledge Cutoff: Aug 2025

Claude Sonnet 4.6 (Anthropic)

Frontier Model Non-Reasoning

Everyday tasks across most use cases.

Knowledge Cutoff: Aug 2025

Claude Haiku 4.5 (Anthropic)

Frontier Model Non-Reasoning

Quick questions and lightweight tasks.

Knowledge Cutoff: July 2025

Claude 4.6 Sonnet (Reasoning) (Anthropic)

Frontier Model Reasoning

Difficult problems that need step-by-step reasoning.

Knowledge Cutoff: Aug 2025

GPT 5.4 (OpenAI)

Frontier Model Reasoning

OpenAI’s coding and reasoning model.

Knowledge Cutoff: Aug 2025

Gemini 3.1 Pro (Google)

Frontier Model Reasoning

Google’s most powerful thinking model.

Knowledge Cutoff: Jan 2025

Gemini 3.5 Flash (Google)

Frontier Model Reasoning

Google’s fast model for agentic and coding workflows.

Knowledge Cutoff: Jan 2026

Gemini 3 Flash (Google)

Frontier Model Reasoning

General purpose model built for speed.

Knowledge Cutoff: Jan 2025

Mistral Large 3 (Mistral)

Open Weight Model Non-Reasoning

Mistral’s 675B parameter flagship model.

Knowledge Cutoff: Oct 2024

Kimi K2.5 (Moonshot, where allowed by law)

Open Weight Model Non-Reasoning

Open weight model that excels at using tools.

Knowledge Cutoff: ~Apr 2024

Llama 4 Maverick (Meta)

Open Weight Model Non-Reasoning

Open weight model for reasoning, math, and general knowledge.

Knowledge Cutoff: Aug 2024

Llama 4 Scout (Meta)

Open Weight Model Non-Reasoning

Multi-document analysis and cross-lingual understanding.

Knowledge Cutoff: Aug 2024

Llama 3.3 70B Instruct (Meta)

Open Weight Model Non-Reasoning

Open weight model for reasoning, math, and general knowledge.

Knowledge Cutoff: Dec 2023

Qwen 3 (Alibaba, where allowed by law)

Open Weight Model Non-Reasoning

235B parameter open weight model for instruction following and reasoning.

Knowledge Cutoff: Oct 2023

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Tips for Selecting the Right Model

Selecting can be tricky. That’s why we encourage you to play and experiment as you build to find the model that is best fit for your context.

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Selection Considerations

Ask yourself what is an ideal response time for your app?

This will allow you to pick larger or smaller models that meet those needs. Claude Sonnet 4.6 offers excellent balance, while Claude Opus 4.6, Gemini 3.1 Pro, and GPT 5.4 prioritize quality over speed. Claude Haiku 4.5 and Gemini 3 Flash excel at speed for simple tasks.

Identify what complexity level is your task?

For simple Q&A or content generation, lighter models like Claude Haiku 4.5 or Gemini 3 Flash may suffice. For balanced everyday tasks, Claude Sonnet 4.6 is ideal. For the most complex multi-step reasoning, choose Claude Opus 4.6, GPT 5.4, or Gemini 3.1 Pro. For agentic and coding workflows at Flash-tier speed, Gemini 3.5 Flash is a strong choice.

What is the level of accuracy you are requiring of your app?

Critical accuracy use cases like data analysis, or HR operations might require Claude Opus 4.6, GPT 5.4, Gemini 3.1 Pro, or other powerful models even if they’re slower. Use cases that require creativity or open ended responses work well with GPT 5.4, Claude Sonnet 4.6, or creative-focused models.

Do you need open weights or source code access?

If you need model customization, local deployment, or transparency into model operations, consider open weight models like Llama 4 series, Qwen 3 (where allowed by law), or Mistral Large 3. For maximum performance and latest capabilities, frontier models like Claude Opus 4.6, GPT 5.4, Claude Sonnet 4.6, or Gemini 3.1 Pro are typically best. Consider your long-term deployment and customization needs when choosing between proprietary and open models.

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Best Practices

Try to match your model with your use case:

Everyday applications: Claude Sonnet 4.6 or Claude Haiku 4.5 provide the best balance of performance and efficiency. Critical/Complex applications: Claude Opus 4.6, GPT 5.4, or Gemini 3.1 Pro for highest accuracy and reasoning capability. Creative applications: GPT 5.4 or Claude Sonnet 4.6 for creative tasks. Problem-solving tools: Claude Opus 4.6, Claude Sonnet 4.6, GPT 5.4, Gemini 3.1 Pro, or Llama 4 Maverick. Document analysis: Claude Opus 4.6, Claude Sonnet 4.6, or Llama 4 Scout for multi-document or cross-lingual analysis. Technical/Coding tasks: Claude Opus 4.6, Claude Sonnet 4.6, GPT 5.4, or Kimi K2.5 (where allowed by law) for tool usage. Educational explanation: Claude Sonnet 4.6, Llama 3.3 70B Instruct, Llama 4 Maverick, or those with strong explanatory capabilities. High-volume applications: Balance quality with speed using Claude Sonnet 4.6, Claude Haiku 4.5, or Gemini 3 Flash. Budget-conscious applications: Claude Haiku 4.5, Qwen 3 (where allowed by law), Mistral Large 3, or other open weight models for cost-effective solutions. Research/Experimentation: Open weight models like Llama 4 series, Qwen 3 (where allowed by law), or Mistral Large 3 for flexibility.

Test out multiple models for apps that you are building:

Changing a model may change performance of an app in Playlab. Test multiple models before finalizing, as performance can vary significantly on your specific tasks. Implement A/B testing as you’re building and testing to continually evaluate model performance. Consider starting with Claude 5.5 Sonnet, the default for new apps, as your baseline for most applications. Test both frontier and open weight models to find the best fit for your needs.

Additional best practices:

We recommend that you remix apps as you’re experimenting to not impact the original app. You can review activity to see how multiple models handle similar tasks. If you’re building a suite of apps we recommend you use faster models like Claude Haiku 4.5 for simple queries and reserve powerful models like Claude Opus 4.6, Claude Sonnet 4.6, GPT 5.4, or Gemini 3.1 Pro for complex tasks. Consider cost implications, as newer frontier models like Claude Opus 4.6, Claude Sonnet 4.6, Gemini 3.1 Pro, and GPT 5.4 may be more expensive but offer better performance. For production apps requiring customization, evaluate open weight models like Qwen 3 (where allowed by law), Mistral Large 3, and Kimi K2.5 (where allowed by law) alongside frontier options. Keep track of which models work best for your specific use cases to build your own selection guidelines.

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FAQ

Will switching models affect my existing app?

Yes, changing the LLM model can impact the performance of your app. Different models have different strengths and trade-offs, so it’s important to test your app with the new model before finalizing the change.

How do I know which model is best for my specific use case?

We recommend experimenting with different models for your specific use case. Consider factors like response time requirements, complexity level of tasks, accuracy needs, and whether you need open weights. You can implement A/B testing to evaluate model performance. For most applications, Claude 5.5 Sonnet, the default for new apps, is a great starting point.

Can I use different models for different parts of my app suite?

Yes! We recommend using faster models like Claude Haiku 4.5 for simple queries and reserving more powerful models like Claude Opus 4.6, Claude Sonnet 4.6, GPT 5.4, Gemini 3.1 Pro, or Claude 4.6 Sonnet (Reasoning) for complex tasks if you’re building a suite of apps.

What is the default model for new apps?

Claude 5.5 Sonnet is the default model for new apps in Playlab. It offers the best balance of intelligence, speed, and cost for most applications. Apps you already have keep the model they use, and you can switch any app to another model at any time.

When should I choose Claude 5.5 Opus vs Claude 5.5 Sonnet vs Claude 5.5 Haiku?

Choose Claude 5.5 Opus for complex projects, agents, and coding. Choose Claude 5.5 Sonnet for everyday tasks and writing with cost efficiency. Choose Claude 5.5 Haiku for high-volume tasks where speed and low cost matter. Claude 5.5 Opus and Claude 5.5 Sonnet create the best looking artifacts. Test each model on your app’s tasks before deciding.

What's the difference between frontier, open weight, and open source models?

Frontier models are cutting-edge proprietary models with the latest capabilities but require API access. Open weight models have publicly available parameters, allowing more control and customization. Open source models provide both weights and training code. Choose based on your needs for performance vs. customization and transparency.

When should I consider open weight models like Llama 4, Qwen 3 (where allowed by law), or Mistral Large 3?

Consider open weight models when you need model customization, local deployment, cost control for high-volume applications, or transparency into model operations. They’re also great for research and experimentation. However, frontier models typically offer better performance for most production applications.

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We Want Your Feedback!

Have you tried building with different LLM models? We’d love to hear about your experience with the new models and which ones work best for your use cases!

Contact us at [e-mail]

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Last updated: 10-21-2026