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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Gemini 4 ArgonGoogleRemove
  3. GLM 5.3 FlashZ.AIRemove
mai-ds-r1:free vs gemini-4-argon vs glm-5.3-flash
Attributemai-ds-r1:freeNot in the catalogueGemini 4 Argongemini-4-argonGLM 5.3 Flashglm-5.3-flash
Pricing
Input—$2.00 / 1M$0.075 / 1M
Output—$10.00 / 1M$0.25 / 1M
Cache Write (5m)—$2.00 / 1M$0.075 / 1M
Cache Write (1h)—$2.00 / 1M$0.075 / 1M
Cache Read—$2.00 / 1M$0.075 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context—1M1M
Max output—N/AN/A
Capabilities
Vision—YesYes
Function Calling—YesYes
JSON Mode—YesYes
Streaming—YesYes
Catalogue
Provider—GoogleZ.AI
Category—chatchat
Charge type—Pay As You GoPay As You Go
Released———
Description
Summary—Gemini 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.