由 1. Model Selection
Cursor supports multiple large language models, which you can configure under Settings → Models. The main categories are:
- OpenAI Models
- GPT-5 (latest and most powerful, excels at complex coding and reasoning)
- GPT-4o, GPT-4.1, GPT-4 Turbo
- GPT-3.5 Turbo (cheap, fast, great for daily code completions)
- Anthropic Claude Models
- Claude 3.5 Sonnet (balanced speed and quality, very strong in coding)
- Claude 3.5 Opus (more powerful, better reasoning, but more expensive)
- Local / Self-Hosted Models (requires API key or local deployment)
- Open-source models such as Llama 3, Mistral
👉 Your choice depends on whether you need code generation, casual Q&A, or deep reasoning.
2. Model Pricing (API Calls)
Pricing depends on the provider account (OpenAI or Anthropic) that you connect to Cursor. Reference prices as of 2025:
- OpenAI GPT-5
- Input (prompt): around $0.01 / 1k tokens
- Output (completion): around $0.03 / 1k tokens
- ⚡ Strongest model in Cursor, but more costly than GPT-4o. Best for complex, multi-file, or architecture-level coding tasks.
- OpenAI GPT-4o
- Input: around $0.005 / 1k tokens
- Output: around $0.015 / 1k tokens
- Anthropic Claude 3.5 Sonnet
- Input: around $0.003 / 1k tokens
- Output: around $0.015 / 1k tokens
- Anthropic Claude 3.5 Opus
- Input: around $0.015 / 1k tokens
- Output: around $0.075 / 1k tokens
- OpenAI GPT-3.5 Turbo (budget-friendly)
- Input: around $0.0005 / 1k tokens
- Output: around $0.0015 / 1k tokens
⚠️ Note: Cursor itself does not charge extra fees for API usage. You must configure your own API keys (OpenAI or Anthropic), and costs are billed directly by the provider.
3. Cursor Pro (Official Subscription)
If you subscribe to Cursor Pro (around $20/month), you get:
- Longer context windows
- Higher usage limits
- Priority access to new features
However, model API calls (GPT-5, GPT-4o, Claude 3.5, etc.) are still billed separately through your provider account. Cursor Pro mainly enhances the IDE experience but does not replace API usage costs.
Cursor Coding Model Comparison (2025)
| Model | Key Features | Pricing (Input / Output) | Best Use Cases | Value Rating |
|---|---|---|---|---|
| GPT-3.5 Turbo | Fast, cheap, decent coverage for code | $0.0005 / $0.0015 per 1k tokens | Daily small features, quick iterations | ⭐⭐⭐⭐💲 (super cost-effective) |
| GPT-4o | OpenAI’s flagship model, multimodal, strong code quality, fast | $0.005 / $0.015 per 1k tokens | Complex project development, debugging, cross-language migration | ⭐⭐⭐⭐⭐ (most balanced) |
| GPT-5 | Latest and most powerful, excels at reasoning, long-context coding, and multi-file generation | ~$0.01 / ~$0.03 per 1k tokens | Architecture-level design, multi-module coding, advanced problem-solving | ⭐⭐⭐⭐⚡ (powerful but higher cost) |
| Claude 3.5 Sonnet | Long context window, excellent for documentation and code explanation, stable logic | $0.003 / $0.015 per 1k tokens | Large projects, understanding codebases, writing tests | ⭐⭐⭐⭐⭐💲 (great for teams) |
| Claude 3.5 Opus | Strongest in reasoning and logic, suitable for architecture design and deep debugging | $0.015 / $0.075 per 1k tokens | High-difficulty algorithms, architecture reviews, cross-disciplinary problems | ⭐⭐⭐ (powerful but expensive) |
| Open-source models (Llama 3, Mistral, etc.) | Self-hosted, free from API fees, but lower quality than premium models | Free (compute costs only) | Local development, privacy-sensitive environments | ⭐⭐💻 (best if you can deploy yourself) |
🔑 Model Selection Tips
- On a budget / beginners → Go with GPT-3.5 Turbo, almost free to use.
- Stable, high-quality coding → GPT-4o is the best balanced default in Cursor.
- Large projects / documentation → Claude 3.5 Sonnet shines with long context.
- Advanced reasoning / architecture → Use Claude 3.5 Opus or GPT-5, but only when needed due to higher costs.
- Privacy / local preference → Consider Llama 3 / Mistral, self-hosted with no API charges.
💰 Monthly Cost Estimation (Based on 22 Workdays)
| Model | Input Cost | Output Cost | Daily Total | Monthly Total | Evaluation |
|---|---|---|---|---|---|
| GPT-3.5 Turbo | $0.025 (50k × 0.0005) | $0.03 (20k × 0.0015) | $0.055 | ≈ $1.2 | Extremely cheap, almost negligible. Great for light usage. |
| GPT-4o | $0.25 (50k × 0.005) | $0.30 (20k × 0.015) | $0.55 | ≈ $12 | Strongly recommended as the main model. High quality at reasonable cost. |
| GPT-5 | $0.50 (50k × 0.01) | $0.60 (20k × 0.03) | $1.10 | ≈ $24 | Powerful and accurate, best for complex or multi-module projects, but more expensive. |
| Claude 3.5 Sonnet | $0.15 (50k × 0.003) | $0.30 (20k × 0.015) | $0.45 | ≈ $10 | Excellent for long-context tasks, suitable for large projects. |
| Claude 3.5 Opus | $0.75 (50k × 0.015) | $1.50 (20k × 0.075) | $2.25 | ≈ $50 | Elite mode. Best for rare, high-difficulty tasks due to high cost. |
| Open-source Models (Llama 3, Mistral, etc.) | ≈ $0 | ≈ $0 | ≈ $0 (excluding compute/electricity) | ≈ $0 | Free to use if self-hosted, but requires GPU/infra setup. |
💡 Cost-Saving Tips
- Use GPT-3.5 Turbo for autocomplete → Token cost is almost negligible.
- Rely on GPT-4o for daily conversations → Stable and efficient for most tasks.
- Switch to Claude 3.5 Sonnet for large projects → Prevents context loss and handles long codebases well.
- Use Claude 3.5 Opus only when stuck → Limit to 10–20% of your workload to avoid overspending.
- Bring in GPT-5 for complex multi-module or architecture-level tasks → Extremely powerful, but about twice the cost of GPT-4o, so reserve it for high-impact work.
- Enable token usage limits → In Settings → Models → Usage, set a monthly cap to avoid budget surprises.
⚙️ Recommended Configuration Example
- Autocomplete →
gpt-3.5-turbo - Default Chat →
gpt-4o - Extra Model →
claude-3.5-sonnet - Advanced Model (manual switch) →
claude-3.5-opus - Premium Model (on-demand) →
gpt-5
✅ With this hybrid setup, your monthly cost stays around $18–25, while giving you access to 90% of flagship-level performance.
You get the best balance: cheap completions, efficient daily coding, long-context support, and the option to bring in GPT-5 whenever you need cutting-edge reasoning or multi-file code generation.