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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. GPT-6 Sol ProOpenAIRemove
  3. Perceptron Mk1.5PerceptronRemove
gpt-6-luna vs gpt-6-sol-pro vs perceptron-mk1.5
AttributeGPT-6 Lunagpt-6-lunaGPT-6 Sol Progpt-6-sol-proPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$0.10 / 1M$2.00 / 1M$0.15 / 1M
Output$0.50 / 1M$10.00 / 1M$1.50 / 1M
Cache Write (5m)$0.10 / 1M$2.00 / 1M$0.15 / 1M
Cache Write (1h)$0.10 / 1M$2.00 / 1M$0.15 / 1M
Cache Read$0.10 / 1M$2.00 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1M1.1M36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderOpenAIOpenAIPerceptron
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
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.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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.