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.

Qwen3.8 27BAlibaba Remove
Perceptron Mk1.5Perceptron Remove
Gemini 4 ArgonGoogle Remove
GLM 5.3 FlashZ.AI Remove

4 is the maximum. Remove one to add another.

qwen3.8-27b vs perceptron-mk1.5 vs gemini-4-argon vs glm-5.3-flash
Attribute	Qwen3.8 27Bqwen3.8-27b	Perceptron Mk1.5perceptron-mk1.5	Gemini 4 Argongemini-4-argon	GLM 5.3 Flashglm-5.3-flash
Pricing
Input	$0.45 / 1M	$0.15 / 1M	$2.00 / 1M	$0.075 / 1M
Output	$3.20 / 1M	$1.50 / 1M	$10.00 / 1M	$0.25 / 1M
Cache Write (5m)	$0.45 / 1M	$0.15 / 1M	$2.00 / 1M	$0.075 / 1M
Cache Write (1h)	$0.45 / 1M	$0.15 / 1M	$2.00 / 1M	$0.075 / 1M
Cache Read	$0.45 / 1M	$0.15 / 1M	$2.00 / 1M	$0.075 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	262K	36.9K	1M	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	Yes	Yes
Function Calling	Yes	No	Yes	Yes
JSON Mode	Yes	No	Yes	Yes
Streaming	Yes	Yes	Yes	Yes
Catalogue
Provider	Alibaba	Perceptron	Google	Z.AI
Category	chat	chat	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-09-25	—	—
Description
Summary	Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	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.