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.

GPT-6 AstraOpenAI Remove
GLM 5.3 FlashZ.AI Remove
Sonar ReasoningPerplexity Remove
Muse Spark 1.3Meta Remove

4 is the maximum. Remove one to add another.

gpt-6-astra vs glm-5.3-flash vs sonar-reasoning vs muse-spark-1.3
Attribute	GPT-6 Astragpt-6-astra	GLM 5.3 Flashglm-5.3-flash	Sonar Reasoningsonar-reasoning	Muse Spark 1.3muse-spark-1.3
Pricing
Input	$10.00 / 1M	$0.075 / 1M	$1.00 / 1M	$1.25 / 1M
Output	$50.00 / 1M	$0.25 / 1M	$5.00 / 1M	$4.25 / 1M
Cache Write (5m)	$10.00 / 1M	$0.075 / 1M	$1.00 / 1M	$1.25 / 1M
Cache Write (1h)	$10.00 / 1M	$0.075 / 1M	$1.00 / 1M	$1.25 / 1M
Cache Read	$10.00 / 1M	$0.075 / 1M	$1.00 / 1M	$1.25 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	1M	127K	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	Yes	Yes	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	OpenAI	Z.AI	Perplexity	Meta
Category	chat	chat	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	—	—	—
Description
Summary	GPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.	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.	—	Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.