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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 Luna ProOpenAIRemove
  2. Gemma 4 26B A4BGoogleRemove
  3. Perceptron Mk1.5PerceptronRemove
gpt-6-luna-pro vs gemma-4-26b-a4b-it vs perceptron-mk1.5
AttributeGPT-6 Luna Progpt-6-luna-proGemma 4 26B A4Bgemma-4-26b-a4b-itPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$0.10 / 1M$0.13 / 1M$0.15 / 1M
Output$0.50 / 1M$0.40 / 1M$1.50 / 1M
Cache Write (5m)$0.10 / 1M$0.13 / 1M$0.15 / 1M
Cache Write (1h)$0.10 / 1M$0.13 / 1M$0.15 / 1M
Cache Read$0.10 / 1M$0.13 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1M262.1K36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderOpenAIGooglePerceptron
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
Description
SummaryGPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier.Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.