GPT-5.2 vs Claude Haiku 4.5
Detailed pricing comparison and cost analysis.
Updated April 2026
Cost Simulator
| Feature | GPT-5.2 | Claude Haiku 4.5 |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Input Price (1M) | $1.75 | $1.00 |
| Output Price (1M) | $14.00 | $5.00 |
| Context Window | 128,000 | 200,000 |
Verdict
GPT-5.2 costs $1.75 per 1M input tokens and $14.00 per 1M output tokens. Claude Haiku 4.5 costs $1.00 per 1M input tokens and $5.00 per 1M output tokens. Claude Haiku 4.5 is 43% cheaper on input tokens than GPT-5.2. For output tokens, Claude Haiku 4.5 is the more affordable option at $5.00/1M vs $14.00.
On context window, Claude Haiku 4.5 supports 200,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-5.2
- ✓ You are already integrated with OpenAI
When to choose Claude Haiku 4.5
- ✓ You need the lowest input token cost ($ 1.00/1M)
- ✓ Your workload is output-heavy — Claude Haiku 4.5 generates text cheaper
- ✓ You need a larger context window (200,000 tokens)
- ✓ You are already integrated with Anthropic
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is GPT-5.2 cheaper than Claude Haiku 4.5? ▼
Claude Haiku 4.5 is cheaper on input tokens at $1.00/1M vs $1.75/1M for GPT-5.2 — a 43% saving.
What is the context window of GPT-5.2 vs Claude Haiku 4.5? ▼
GPT-5.2 has a 128,000-token context window. Claude Haiku 4.5 has a 200,000-token context window. Claude Haiku 4.5 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-5.2 or Claude Haiku 4.5? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Claude Haiku 4.5 is the cheaper option. For maximum context length, Claude Haiku 4.5 supports 200,000 tokens. Use the comparison table above to find the right fit for your workload.