Claude Haiku 5.5 wins on coding (86 vs 84). For most workflows, Claude Haiku 5.5 is the stronger default — anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
The safest Claude Haiku 5.5 vs GPT-6 Luna default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Claude Haiku 5.5 is the strongest answer here for Claude Haiku 5.5 vs GPT-6 Luna — pick it when quality of output matters more than the $0.10/1M/1M input you pay for it.
Claude Sonnet 5.5 is the cheaper way in for Claude Haiku 5.5 vs GPT-6 Luna, at $2.00/1M/1M input against Claude Haiku 5.5's $0.10/1M/1M.
GPT-6 Luna is the fastest of these for Claude Haiku 5.5 vs GPT-6 Luna — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Claude Haiku 5.5 leads on coding with a score of 86 vs 84 for GPT-6 Luna.
GPT-6 Luna has the larger context window: 1.05M vs 1M for Claude Haiku 5.5.
Both models are similarly priced — the decision comes down to capability, not cost.
Claude Haiku 5.5 is the safer default: it is built for high-volume tool use, sub-agents and everyday tasks on a tight budget, which covers most of what people bring to this comparison.
GPT-6 Luna earns its place when your work is mostly high-volume and focused tasks where cost per call decides the model, even though it loses the overall count here.
Both models serve different primary workflows — Claude Haiku 5.5 for high-volume tool use and sub-agents and everyday tasks on a tight budget, GPT-6 Luna for high-volume and focused tasks where cost per call decides the model — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the Claude Haiku 5.5 vs GPT-6 Luna answer changes when cost, speed, or long-document depth leads the decision.
Anthropic / Budget / Oct 10, 2026
Anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
Where the Claude Haiku 5.5 vs GPT-6 Luna recommendation shifts once you weigh price or latency differently.
Anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
OpenAI's budget tier at half the old price.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Claude Haiku 5.5Anthropic | $0.10/1M | $0.50/1M | $2.00 | 1M tokens | Very fast | 86 | 84 | 82 |
| GPT-6 LunaOpenAI | $0.10/1M | $0.50/1M | $2.00 | 1.1M tokens | Very fast | 84 | 82 | 80 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for Claude Haiku 5.5 vs GPT-6 Luna, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for Claude Haiku 5.5 vs GPT-6 Luna: 86/100 on coding, with the widest margin of anything in this line-up.
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
The cheapest way to put an Anthropic model in a high-volume pipeline. Keep requests under 100K tokens to stay on the low rate, and set effort per task — at low effort it is a fast classifier, at max it handles real tool-use work.
Full pricing, benchmark table and release notes on the Claude Haiku 5.5 page.
The fastest model in this shortlist for Claude Haiku 5.5 vs GPT-6 Luna. Pick it when turnaround is what your readers or users notice.
OpenAI's September 22, 2026 low-cost reasoning model, replacing GPT-5.6 Luna at $0.10/$0.50 per 1M — half the predecessor's price, with the same 1.05M context.
You are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index.
A cheaper Luna rather than a smarter one. At $0.10/$0.50 it matches Claude Haiku 5.5 on price, but independent scoring puts Haiku 5.5 slightly ahead; choose Luna when you are already on the OpenAI stack.
Full pricing, benchmark table and release notes on the GPT-6 Luna page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Claude Haiku 5.5 wins on more of the categories we score — coding, writing, budget — so it is the better default of the two. GPT-6 Luna is the better pick when your work is mostly high-volume and focused tasks where cost per call decides the model. Neither is universally "better": Claude Haiku 5.5 is aimed at high-volume tool use and sub-agents and everyday tasks on a tight budget, GPT-6 Luna at high-volume and focused tasks where cost per call decides the model.
Both models are similarly priced at $0.1/1M input tokens. The decision should come down to capability, not cost.
GPT-6 Luna has the larger context window at 1.05M tokens vs Claude Haiku 5.5's 1M. For large document analysis, GPT-6 Luna is the stronger pick.
Claude Haiku 5.5 is better for coding with a score of 86 vs GPT-6 Luna's 84 (out of 100). Claude Opus 5.5 is the overall coding leader in this directory at 100/100.
Both Claude Haiku 5.5 and GPT-6 Luna have similar speed profiles — rated very fast. Neither will be the bottleneck if latency is your deciding factor.
Long prompts cost five times more: above 100K input tokens the rate becomes $0.50/$2.50. Effort matters a great deal: Terminal-Bench 4.0 is 12.8% at low effort against 39.2% at max. Avoid it if your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better. That is the main case for looking at GPT-6 Luna instead.
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41). Prompts above 272K input tokens are billed at a higher rate. Avoid it if you are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index. Against Claude Haiku 5.5 specifically, the gap shows up most on coding (86 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. Claude Haiku 5.5 runs $2.00 (at $0.1/1M in and $0.5/1M out); GPT-6 Luna runs $2.00 (at $0.1/1M in and $0.5/1M out). The gap is small enough that price should not decide this one. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is Claude Haiku 5.5 for high-volume tool use and sub-agents and everyday tasks on a tight budget, with GPT-6 Luna handling high-volume and focused tasks where cost per call decides the model. Since Claude Haiku 5.5 is both the stronger and the cheaper option here, a split mainly makes sense if GPT-6 Luna covers a capability you specifically need.