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GPT-6 Luna vs Claude Haiku 4.5
A straight cost comparison of GPT-6 Luna (OpenAI) and Claude Haiku 4.5 (Anthropic), per 1,000,000 tokens, verified October 2026.
Rate-by-rate comparison
| Metric | GPT-6 Luna | Claude Haiku 4.5 | Winner |
|---|---|---|---|
| Input / 1M | $0.10 | $1 | GPT-6 Luna |
| Cached input / 1M | $0.01 | $0.10 | GPT-6 Luna |
| Cache write / 1M | $0.125 | $1.25 | GPT-6 Luna |
| Output / 1M | $0.50 | $5 | GPT-6 Luna |
| Context window | 1,050,000 | 200,000 | GPT-6 Luna |
| Batch API | Yes | Yes | Tie |
| Long-context tier | > 272,000 | None | — |
For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.
Blended cost: 1M input + 250K output
| Model | Blended cost | Difference |
|---|---|---|
| GPT-6 Luna | $0.225 | Cheaper |
| Claude Haiku 4.5 | $2.25 | +$2.02 |
Three workloads, two bills
| Workload | GPT-6 Luna | Claude Haiku 4.5 | Winner |
|---|---|---|---|
| Support chat 1,000 requests · 4K input / 600 output | $0.70 | $7 | GPT-6 Luna |
| RAG with caching 1,000 requests · 50K input (45K cached) / 1K output | $1.46 | $14.55 | GPT-6 Luna |
| Nightly batch job 10,000 requests · 10K input / 2K output | $10 | $100 | GPT-6 Luna |
Which one should you pick?
GPT-6 Luna wins on support chat, cached RAG, nightly batch job, while Claude Haiku 4.5 wins on none of the three workloads above.
Beyond price, the two differ on input rate ($0.10 vs $1); output rate ($0.50 vs $5); cached-input rate ($0.01 vs $0.10); cache-write rate ($0.125 vs $1.25); context window (1,050,000 vs 200,000); long-context tier (yes, above 272,000 vs none).
Batch mode is available on GPT-6 Luna and Claude Haiku 4.5, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.
FAQ
Is GPT-6 Luna cheaper than Claude Haiku 4.5?
On a blended 1M-input-plus-250K-output workload, GPT-6 Luna is cheaper by 90% ($0.225 vs $2.25). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.
Which handles longer prompts, GPT-6 Luna or Claude Haiku 4.5?
Claude Haiku 4.5 has the larger context window (1,050,000 vs 200,000 tokens). Watch the long-context threshold on GPT-6 Luna: rates rise once input passes it.
Do both models support prompt caching?
GPT-6 Luna bills cached reads at $0.01 per 1M; Claude Haiku 4.5 at $0.10.