Is Claude Haiku 5.5 cheaper than GPT-6 Luna?

Not at the base rate — both charge exactly $0.10 per million input tokens and $0.50 per million output tokens. The difference appears on long prompts: Haiku 5.5's price jumps 5x past 100,000 tokens, while GPT-6 Luna's increase is smaller and starts later, at 272,000 tokens, making Luna cheaper for long-context workloads.

What's the monthly cost at 100M input and 30M output tokens?

At the shared base rate, 100M input tokens cost $10.00 and 30M output tokens cost $15.00, for a total of $25.00 per month on either model — identical, as long as individual requests stay under each model's long-context pricing threshold.

Do these models have the same context window?

Not exactly. Public pricing tables point to a lower-tier pricing cutoff around 100,000 tokens for Claude Haiku 5.5 and 272,000 tokens for GPT-6 Luna, suggesting Luna may support longer efficient-rate prompts, though official maximum context window specs should be checked directly with each provider.

Which model is better for output-heavy workloads?

Since both models charge the same $0.50 per million output tokens at the base tier, raw output pricing won't differentiate them for typical workloads. The decisive factor is token efficiency and whether your prompts exceed each model's long-context threshold, where Luna's smaller surcharge gives it an edge.

HEAD-TO-HEAD · BUDGET-TIER · VERIFIED OCTOBER 13, 2026

Claude Haiku 5.5 vs GPT-6 Luna: which one is actually cheaper?

Claude Haiku 5.5 and GPT-6 Luna launched days apart with identical headline rates: $0.10 per million input tokens and $0.50 per million output tokens. On paper it's a dead heat — but tiered long-context pricing and token efficiency can quietly separate the two in practice.

Spec	Claude Haiku 5.5	GPT-6 Luna
Input / 1M tokens	$0.10	$0.10
Output / 1M tokens	$0.50	$0.50
Context window	200K (uncertain)	400K (uncertain)

The output price gap

There is no output-price gap at the headline rate — both models charge $0.50 per million output tokens. The real divergence shows up at longer prompts: independent pricing breakdowns show that past a certain input length, Haiku 5.5's rates jump 5x while GPT-6 Luna's increase is far smaller, meaning output and input costs can diverge sharply on long-context workloads even though short-prompt pricing is identical.

Context window

Exact context window specs aren't fully confirmed in our sanity check, but reporting around the launch indicates a key pricing boundary for Claude Haiku 5.5 at 100,000 tokens and for GPT-6 Luna at 272,000 tokens, after which input and output rates rise. Treat the context window figures above as approximate until confirmed against official model cards.

Worked example

At the shared base rate of $0.10/M input and $0.50/M output: 100M input tokens cost 100 x $0.10 = $10.00, and 30M output tokens cost 30 x $0.50 = $15.00. That's $10.00 + $15.00 = $25.00 per month for Claude Haiku 5.5, and identically $25.00 per month for GPT-6 Luna, assuming all requests stay within each model's lower pricing tier (under 100K tokens per request for Haiku, under 272K for Luna). If individual requests regularly exceed those thresholds, Luna becomes meaningfully cheaper since its long-context surcharge is smaller.

Prices from the LLM Price Watch daily tracker, 2026-10-13. Prices change; use the calculator with your own usage for an exact comparison, or see the full price table for every tracked model.