Overview
BoldCreate supports multiple premium AI models, each suited to different kinds of development work. Some models are optimized for speed and quick tasks, while others offer deep reasoning for complex problems. This guide helps you pick the right model based on what you need to accomplish.
Note: The models listed in this guide are premium models available in BoldCreate. Different models consume different amounts of your usage allowance.
Models by task
Use the table below to quickly find the right model for your task.
| Model | Best task category | Strengths |
|---|---|---|
| Claude Haiku 4.5 | Fast help with simple or repetitive tasks | Fast, reliable answers to lightweight coding questions |
| Claude Opus 4.1 | Deep reasoning and debugging | Complex problem-solving, sophisticated reasoning |
| Claude Opus 4.5 | Deep reasoning and debugging | Complex problem-solving, sophisticated reasoning |
| Claude Sonnet 4.5 | General-purpose coding and agent tasks | Balanced speed and reasoning for everyday workflows |
| Claude Sonnet 4.6 | General-purpose coding and agent tasks | More reliable completions and smarter reasoning |
| Gemini 3 Flash (Preview) | Fast help with simple or repetitive tasks | Fast answers for lightweight coding questions |
| Gemini 3.1 Flash-Lite (Preview) | Fast help with simple or repetitive tasks | Low-latency responses for quick edits and prototyping |
| Gemini 3.1 Pro (Preview) | Deep reasoning and debugging | Precise tool use, effective edit-then-test workflows |
| GPT-4.1 | General-purpose coding and writing | Consistent, accurate code completions and explanations |
| GPT-5 | Deep reasoning and debugging | Multi-step problem solving, architecture-level analysis |
| GPT-5 mini | General-purpose coding and writing | Fast, accurate completions across languages and frameworks |
| GPT-5.4 Mini | Agentic software development | Fast and efficient for coding and multi-step tasks |
| GPT-5.4 Nano | Fast help with simple or repetitive tasks | Low-cost model for simple, high-volume tasks |
| GPT-5.1 Codex | Agentic software development | Code-focused agentic tasks and complex refactoring |
| GPT-5.2 | Deep reasoning and debugging | Multi-step reasoning and code analysis |
| GPT-5.2 Codex | Agentic software development | Agentic coding tasks with high precision |
| GPT-5.3 Codex | Agentic software development | High-quality output on complex engineering tasks |
| GPT-5.4 | Deep reasoning and debugging | Complex reasoning, code analysis, technical decisions |
Task: Fast help with simple or repetitive tasks
These models are optimized for speed. Use them for quick edits, small utility functions, syntax questions, and lightweight prototyping.
Recommended models
| Model | Description |
|---|---|
| Claude Haiku 4.5 | Balances fast responses with quality output. Ideal for small tasks and lightweight code explanations. |
| Gemini 3 Flash (Preview) | Fast answers for straightforward coding tasks with minimal overhead. |
| Gemini 3.1 Flash-Lite (Preview) | Low-latency responses designed for quick edits and rapid iteration. |
| GPT-5.4 Nano | Cost-efficient option for simple, high-volume tasks and quick helper tasks. |
When to use these models
- Write or edit small functions or utility code
- Ask quick syntax or language questions
- Prototype ideas with minimal setup
- Get fast feedback on simple prompts or edits
When to use a different model
For complex refactoring, architectural decisions, or multi-step logic, see Deep reasoning and debugging. For general development work, see General-purpose coding and writing.
Task: General-purpose coding and writing
Use these models for common development tasks that need a balance of quality, speed, and reliability. These are good defaults when you don’t have a specific requirement.
Recommended models
| Model | Description |
|---|---|
| GPT-4.1 | Reliable default for most coding and writing tasks. Consistent, accurate, and works well across languages and frameworks. |
| GPT-5 mini | Fast and accurate for general coding tasks. Handles multimodal input and works well across languages and frameworks. |
| Claude Sonnet 4.5 | Strong general-purpose model with balanced reasoning speed. Good for everyday workflows and moderate complexity tasks. |
| Claude Sonnet 4.6 | Improves on Sonnet 4.5 with more reliable completions and smarter reasoning. |
When to use these models
- Write or review functions, short files, or code diffs
- Generate documentation, comments, or summaries
- Explain errors or unexpected behavior
- Handle day-to-day development tasks
When to use a different model
For complex refactoring or architectural decisions, see Deep reasoning and debugging. For fast, lightweight tasks, see Fast help with simple or repetitive tasks.
Task: Deep reasoning and debugging
These models handle tasks that require step-by-step reasoning, high-context awareness, or complex decision-making. Use them when you need structured analysis, multi-file understanding, or thorough explanations.
Recommended models
| Model | Description |
|---|---|
| Claude Opus 4.1 | Anthropic’s powerful reasoning model. Suited for complex problem-solving and sophisticated analysis. |
| Claude Opus 4.5 | Delivers deep reasoning for challenging tasks and intricate debugging scenarios. |
| Gemini 3.1 Pro (Preview) | High tool precision with effective edit-then-test workflows and strong context handling. |
| GPT-5 | Deep reasoning across large codebases. Ideal for multi-step problem solving and architecture-level analysis. |
| GPT-5.2 | Strong reasoning model for complex code analysis and technical decision-making. |
| GPT-5.4 | Great at complex reasoning, code analysis, and technical decisions. |
When to use these models
- Debug complex issues spanning multiple files
- Refactor large or interconnected codebases
- Plan features or architecture across system layers
- Analyze logs, performance data, or system behavior
- Weigh trade-offs between libraries, patterns, or design approaches
When to use a different model
For fast iteration or lightweight tasks, see Fast help with simple or repetitive tasks. For general development, see General-purpose coding and writing.
Task: Agentic software development
These models are designed for agent-driven workflows where the model takes a sequence of actions — such as reading files, running tools, and applying changes — to complete a larger task autonomously.
Recommended models
| Model | Description |
|---|---|
| GPT-5.4 Mini | Fast and efficient for coding and multi-step tasks. |
| GPT-5.1 Codex | Purpose-built for software engineering workflows. Strong at refactoring, code maintenance, and adherence to coding standards. |
| GPT-5.2 Codex | High-precision agentic coding tasks with reliable multi-step execution. |
| GPT-5.3 Codex | Delivers higher-quality code on complex engineering tasks like features, tests, debugging, refactoring, and reviews. |
When to use these models
- Automate multi-step code changes across files
- Run agent-driven refactoring or migration tasks
- Generate tests and apply fixes in an automated loop
- Perform large-scale code maintenance with consistent standards
When to use a different model
For single-step reasoning or debugging, see Deep reasoning and debugging. For quick one-off tasks, see Fast help with simple or repetitive tasks.
Next steps
If you’re not sure which model to start with, GPT-4.1 or Claude Sonnet 4.6 are good general-purpose defaults. Switch to a deeper reasoning model like GPT-5 or Claude Opus 4.5 when a task requires more thorough analysis.
- To get started with BoldCreate, see Quick Start