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.

Gemini 3.5 TranscribeGoogle Remove
GPT-6.1 SolOpenAI Remove
Perceptron Mk1.5Perceptron Remove
GLM 5.3 FlashZ.AI Remove

4 is the maximum. Remove one to add another.

gemini-3.5-transcribe vs gpt-6.1-sol vs perceptron-mk1.5 vs glm-5.3-flash
Attribute	Gemini 3.5 Transcribegemini-3.5-transcribe	GPT-6.1 Solgpt-6.1-sol	Perceptron Mk1.5perceptron-mk1.5	GLM 5.3 Flashglm-5.3-flash
Pricing
Input	— Not priced per input token	$2.00 / 1M	$0.15 / 1M	$0.075 / 1M
Output	— Not priced per output token	$10.00 / 1M	$1.50 / 1M	$0.25 / 1M
Cache Write (5m)	Not applicable	$2.00 / 1M	$0.15 / 1M	$0.075 / 1M
Cache Write (1h)	Not applicable	$2.00 / 1M	$0.15 / 1M	$0.075 / 1M
Cache Read	Not applicable	$2.00 / 1M	$0.15 / 1M	$0.075 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	98.3K	1M	36.9K	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	Yes	No	Yes
Function Calling	Yes	Yes	No	Yes
JSON Mode	No	Yes	No	Yes
Streaming	No	Yes	Yes	Yes
Catalogue
Provider	Google	OpenAI	Perceptron	Z.AI
Category	voice	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	—	2026-09-25	—
Description
Summary	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	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.