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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. Gemini 4 ArgonGoogleRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. Perceptron Mk1.5PerceptronRemove
gemini-4-argon vs glm-5.3-flash vs perceptron-mk1.5
AttributeGemini 4 Argongemini-4-argonGLM 5.3 Flashglm-5.3-flashPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$2.00 / 1M$0.075 / 1M$0.15 / 1M
Output$10.00 / 1M$0.25 / 1M$1.50 / 1M
Cache Write (5m)$2.00 / 1M$0.075 / 1M$0.15 / 1M
Cache Write (1h)$2.00 / 1M$0.075 / 1M$0.15 / 1M
Cache Read$2.00 / 1M$0.075 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderGoogleZ.AIPerceptron
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
Description
SummaryGemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.