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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. GPT-6 LunaOpenAIRemove
  2. MAI-Transcribe 2MicrosoftRemove
  3. Gemini 3.5 TranscribeGoogleRemove
  4. Perceptron Mk1.5PerceptronRemove

4 is the maximum. Remove one to add another.

gpt-6-luna vs mai-transcribe-2 vs gemini-3.5-transcribe vs perceptron-mk1.5
AttributeGPT-6 Lunagpt-6-lunaMAI-Transcribe 2mai-transcribe-2Gemini 3.5 Transcribegemini-3.5-transcribePerceptron Mk1.5perceptron-mk1.5
Pricing
Input$0.10 / 1M$0 / 1M$0 / 1M$0.15 / 1M
Output$0.50 / 1M$0 / 1M$0 / 1M$1.50 / 1M
Cache Write (5m)$0.10 / 1MNot applicableNot applicable$0.15 / 1M
Cache Write (1h)$0.10 / 1MNot applicableNot applicable$0.15 / 1M
Cache Read$0.10 / 1MNot applicableNot applicable$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1MN/A98.3K36.9K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesNoYesNo
JSON ModeYesNoNoNo
StreamingYesNoNoYes
Catalogue
ProviderOpenAIMicrosoftGooglePerceptron
Categorychatvoicevoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-032026-09-252026-09-25
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.Microsoft MAI-Transcribe-2 speech-to-text. Billed per second of audio.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.