GPT-6 Luna vs Claude Haiku 5.5
Compare GPT-6 Luna vs Claude Haiku 5.5 API pricing, token costs, context windows, and latency. See which model is cheaper and better for your stack.
GPT-6 Luna charges $0.10/1M input and $0.50/1M output tokens, compared to Claude Haiku 5.5 at $0.10/1M input and $0.50/1M output. GPT-6 Luna is 1.0x cheaper on input tokens. In reasoning benchmarks, Claude Haiku 5.5 holds the higher AA Intelligence Index rating (36/100). For latency-critical streaming, GPT-6 Luna delivers 103 t/s (77.0s TTFT) while Claude Haiku 5.5 provides 256 t/s (186.0s TTFT).
Full Metric & Specification Comparison
| Metric | GPT-6 Luna | Claude Haiku 5.5 | Advantage |
|---|---|---|---|
| Provider | OpenAI | Anthropic | - |
| Input Token Cost (1M) | $0.100 | $0.100 | Tie |
| Output Token Cost (1M) | $0.500 | $0.500 | Tie |
| Context Window | 1,050k tokens | 1,000k tokens | GPT-6 Luna |
| AA Intelligence Index | 28/100 | 36/100 | Claude Haiku 5.5 |
| Streaming Latency | Fast | Ultra-Fast | - |
Key Architectural Takeaways
- Input Token Cost: GPT-6 Luna is $0.10/1M vs Claude Haiku 5.5 at $0.10/1M
- Output Token Cost: GPT-6 Luna is $0.50/1M vs Claude Haiku 5.5 at $0.50/1M
- Context Window: GPT-6 Luna supports 1,050k tokens vs Claude Haiku 5.5 with 1,000k tokens
- Benchmark Intelligence Rating: GPT-6 Luna scores 28/100 vs Claude Haiku 5.5 at 36/100 (AA Index v5)
- Inference Latency: GPT-6 Luna is rated Fast vs Claude Haiku 5.5 rated Ultra-Fast
Calculate Your Team's Exact Bill Difference
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Frequently Asked Questions
Is GPT-6 Luna cheaper than Claude Haiku 5.5?
GPT-6 Luna is significantly more economical, charging $0.10/1M input compared to $0.10/1M for Claude Haiku 5.5.
Which model should I choose for production?
If your primary constraint is API cost and high query throughput, choose GPT-6 Luna. If you require peak reasoning accuracy and complex tool use, Claude Haiku 5.5 is recommended.
How does context window compare between GPT-6 Luna and Claude Haiku 5.5?
GPT-6 Luna offers the larger context window (1,050k tokens), allowing you to pass significantly larger codebases or documents without chunking.
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