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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. Transcribe 1 ProFish AudioRemove
  2. GPT-6 LunaOpenAIRemove
  3. S1Fish AudioRemove
  4. GPT-6 Sol ProOpenAIRemove

4 is the maximum. Remove one to add another.

transcribe-1-pro vs gpt-6-luna vs s1 vs gpt-6-sol-pro
AttributeTranscribe 1 Protranscribe-1-proGPT-6 Lunagpt-6-lunaS1s1GPT-6 Sol Progpt-6-sol-pro
Pricing
Input$0 / 1M$0.10 / 1M$0 / 1M$2.00 / 1M
Output$0 / 1M$0.50 / 1M$0 / 1M$10.00 / 1M
Cache Write (5m)Not applicable$0.10 / 1MNot applicable$2.00 / 1M
Cache Write (1h)Not applicable$0.10 / 1MNot applicable$2.00 / 1M
Cache ReadNot applicable$0.10 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1.1MN/A1.1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesNoYes
Function CallingNoYesNoYes
JSON ModeNoYesNoYes
StreamingNoYesNoYes
Catalogue
ProviderFish AudioOpenAIFish AudioOpenAI
Categoryvoicechatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-24—2026-07-29—
Description
SummaryFish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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 S1 text-to-speech. Billed per UTF-8 byte of input text.GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex and demanding tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is particularly well suited for agentic coding, long-horizon software engineering, professional analysis, and complex automated workflows where solution quality takes priority over latency and cost.