Claude 3.5 Sonnet vs GPT-4 Turbo
Claude 3.5 Sonnet vs GPT-4 Turbo: Claude 3.5 Sonnet is cheaper for input-heavy usage ($3.00/M vs $10.00/M input tokens), while Claude 3.5 Sonnet is better for long-context tasks (200,000 tokens).
Direct answer: choose Claude 3.5 Sonnet for lower token spend and choose Claude 3.5 Sonnet when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Claude 3.5 Sonnet
GPT-4 Turbo
Cost Differences
GPT-4 Turbo costs more than Claude 3.5 Sonnet
Quick Recommendation
Winner for direct API pricing: Claude 3.5 Sonnet. At the default workload, Claude 3.5 Sonnet saves about $43.50/month ($529.25/year) versus GPT-4 Turbo.
Feature Comparison
| Feature | Claude 3.5 Sonnet | GPT-4 Turbo |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input Price | $3.00/1M tokens | $10.00/1M tokens |
| Output Price | $15.00/1M tokens | $30.00/1M tokens |
| Context Window | 200,000 tokens | 128,000 tokens |
| Max Output | 8,192 tokens | 4,096 tokens |
| Category | balanced | flagship |
| Capabilities | textvisioncode | textvisioncode |
| Release Date | 10/22/2024 | 4/9/2024 |
Claude 3.5 Sonnet vs GPT-4 Turbo: Which Should You Choose?
Choosing between Claude 3.5 Sonnet and GPT-4 Turbo depends on your priorities: cost efficiency, context length, or raw capability. Claude 3.5 Sonnet is the more affordable option at $3.00/1M input tokens — 70% cheaper than GPT-4 Turbo. Meanwhile, Claude 3.5 Sonnet offers a significantly larger context window at 200,000 tokens vs 128,000 for GPT-4 Turbo.
These models come from different providers — Anthropic and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Anthropic, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Claude 3.5 Sonnet is a balanced model while GPT-4 Turbo is flagship. This means they're optimized for different workloads. GPT-4 Turbo targets more demanding workloads, while Claude 3.5 Sonnet provides a cost-effective option for everyday tasks.
Output costs matter too. Claude 3.5 Sonnet charges $15.00/1M output tokens vs $30.00 for GPT-4 Turbo. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Claude 3.5 Sonnet has the edge here at $15.00/1M output tokens.
Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.
Best Use Cases
Choose Claude 3.5 Sonnet when:
- • Budget is a primary concern
- • You need a larger context window (200,000 tokens)
- • You need longer outputs (up to 8,192 tokens)
- • You're already using Anthropic's API ecosystem
Choose GPT-4 Turbo when:
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Claude 3.5 Sonnet
- • Input pricing: $3.00/M tokens
- • Output pricing: $15.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Trade-offs are minor in this matchup.
GPT-4 Turbo
- • Input pricing: $10.00/M tokens
- • Output pricing: $30.00/M tokens
- • Context window: 128,000 tokens
- • Max output: 4,096 tokens
Watch out for
- • Higher input cost than Claude 3.5 Sonnet
- • Higher output cost than Claude 3.5 Sonnet
- • Smaller context window than Claude 3.5 Sonnet
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Claude 3.5 Sonnet (Anthropic)
GPT-4 Turbo (OpenAI)
Start using Claude 3.5 Sonnet today
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Claude 3.5 Sonnet or GPT-4 Turbo?▼
What is the context window difference between Claude 3.5 Sonnet and GPT-4 Turbo?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Anthropic and OpenAI API pricing beyond this model matchup?▼
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