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.

GLM 5.3 FlashZ.AI Remove
mai-ds-r1:freeNot in the catalogue Remove
Gemini 4 ArgonGoogle Remove
Perceptron Mk1.5Perceptron Remove

4 is the maximum. Remove one to add another.

glm-5.3-flash vs mai-ds-r1:free vs gemini-4-argon vs perceptron-mk1.5
Attribute	GLM 5.3 Flashglm-5.3-flash	mai-ds-r1:freeNot in the catalogue	Gemini 4 Argongemini-4-argon	Perceptron Mk1.5perceptron-mk1.5
Pricing
Input	$0.075 / 1M	—	$2.00 / 1M	$0.15 / 1M
Output	$0.25 / 1M	—	$10.00 / 1M	$1.50 / 1M
Cache Write (5m)	$0.075 / 1M	—	$2.00 / 1M	$0.15 / 1M
Cache Write (1h)	$0.075 / 1M	—	$2.00 / 1M	$0.15 / 1M
Cache Read	$0.075 / 1M	—	$2.00 / 1M	$0.15 / 1M
Web Search	$0 / 1M	—	$0 / 1M	$0 / 1M
Context
Max context	1M	—	1M	36.9K
Max output	N/A	—	N/A	N/A
Capabilities
Vision	Yes	—	Yes	No
Function Calling	Yes	—	Yes	No
JSON Mode	Yes	—	Yes	No
Streaming	Yes	—	Yes	Yes
Catalogue
Provider	Z.AI	—	Google	Perceptron
Category	chat	—	chat	chat
Charge type	Pay As You Go	—	Pay As You Go	Pay As You Go
Released	—	—	—	2026-09-25
Description
Summary	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.	—	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.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.