Skip to content

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.

  1. GPT-6 LunaOpenAIRemove
  2. Transcribe 1 ProFish AudioRemove
  3. S2 ProFish AudioRemove
  4. Claude Opus 5.5AnthropicRemove

4 is the maximum. Remove one to add another.

gpt-6-luna vs transcribe-1-pro vs s2-pro vs claude-opus-5.5
AttributeGPT-6 Lunagpt-6-lunaTranscribe 1 Protranscribe-1-proS2 Pros2-proClaude Opus 5.5claude-opus-5.5
Pricing
Input$0.10 / 1M$0 / 1M$0 / 1M$4.00 / 1M
Output$0.50 / 1M$0 / 1M$0 / 1M$20.00 / 1M
Cache Write (5m)$0.10 / 1MNot applicableNot applicable$5.00 / 1M
Cache Write (1h)$0.10 / 1MNot applicableNot applicable$8.00 / 1M
Cache Read$0.10 / 1MNot applicableNot applicable$0.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1MN/AN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoNoYes
Function CallingYesNoNoYes
JSON ModeYesNoNoYes
StreamingYesNoNoYes
Catalogue
ProviderOpenAIFish AudioFish AudioAnthropic
Categorychatvoicevoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-242026-07-29—
Description
SummaryGPT-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 Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.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.