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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. Perceptron Mk1.5PerceptronRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. GPT-6 LunaOpenAIRemove
  4. GLM 5 TurboZ.AIRemove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs gemini-3.5-transcribe vs gpt-6-luna vs glm-5-turbo
AttributePerceptron Mk1.5perceptron-mk1.5Gemini 3.5 Transcribegemini-3.5-transcribeGPT-6 Lunagpt-6-lunaGLM 5 Turboglm-5-turbo
Pricing
Input$0.15 / 1M— Not priced per input token$0.10 / 1M$0.96 / 1M
Output$1.50 / 1M— Not priced per output token$0.50 / 1M$3.20 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$0.10 / 1M$0.96 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$0.10 / 1M$0.96 / 1M
Cache Read$0.15 / 1MNot applicable$0.10 / 1M$0.96 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context36.9K98.3K1.1M202.8K
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeNoNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderPerceptronGoogleOpenAIZ.AI
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-252026-09-25——
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.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.GLM-5 Turbo is a high-performance model from Z.ai optimized for fast inference and agent-driven workflows. Designed for real-world environments such as OpenClaw scenarios, it delivers strong performance across long execution chains and complex task pipelines. The model features improved instruction decomposition, tool integration, scheduled and persistent execution, and enhanced stability for extended multi-step tasks, making it well suited for autonomous agents and production automation workflows.