Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

GPT-6 LunaOpenAI Remove
S2 ProFish Audio Remove
Perceptron Mk1.5Perceptron Remove
Claude Opus 5.5Anthropic Remove

4 is the maximum. Remove one to add another.

gpt-6-luna vs s2-pro vs perceptron-mk1.5 vs claude-opus-5.5
Attribute	GPT-6 Lunagpt-6-luna	S2 Pros2-pro	Perceptron Mk1.5perceptron-mk1.5	Claude Opus 5.5claude-opus-5.5
Pricing
Input	$0.10 / 1M	$0 / 1M	$0.15 / 1M	$4.00 / 1M
Output	$0.50 / 1M	$0 / 1M	$1.50 / 1M	$20.00 / 1M
Cache Write (5m)	$0.10 / 1M	Not applicable	$0.15 / 1M	$5.00 / 1M
Cache Write (1h)	$0.10 / 1M	Not applicable	$0.15 / 1M	$8.00 / 1M
Cache Read	$0.10 / 1M	Not applicable	$0.15 / 1M	$0.40 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1.1M	N/A	36.9K	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	No	Yes
Function Calling	Yes	No	No	Yes
JSON Mode	Yes	No	No	Yes
Streaming	Yes	No	Yes	Yes
Catalogue
Provider	OpenAI	Fish Audio	Perceptron	Anthropic
Category	chat	voice	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-07-29	2026-09-25	—
Description
Summary	GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.	Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Claude Opus 5.5 is Anthropic's flagship model for advanced reasoning, coding, and long-horizon agentic workflows, succeeding Opus 5. It excels at multi-step changes across large codebases, code review and bug detection, financial and scientific analysis, and understanding dense charts, diagrams, and screenshots, with stronger grounding when reporting figures and citing sources. Compared with Opus 5, it completes comparable tasks with fewer steps and lower token usage while providing clearer, more concise progress reporting. With adaptive thinking and configurable effort levels, Opus 5.5 can balance reasoning depth, latency, and cost, making it well suited for both demanding autonomous workflows and latency-sensitive professional tasks.