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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.

ERNIE Speed 8KBaidu Remove
GLM 5.3Z.AI Remove
GLM 5.3 FlashZ.AI Remove

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ERNIE-Speed-8K vs glm-5.3 vs glm-5.3-flash
Attribute	ERNIE Speed 8KERNIE-Speed-8K	GLM 5.3glm-5.3	GLM 5.3 Flashglm-5.3-flash
Pricing
Input	$1.46 / 1M	$1.40 / 1M	$0.075 / 1M
Output	$2.92 / 1M	$4.40 / 1M	$0.25 / 1M
Cache Write (5m)	$1.457 / 1M	$1.40 / 1M	$0.075 / 1M
Cache Write (1h)	$1.457 / 1M	$1.40 / 1M	$0.075 / 1M
Cache Read	$1.457 / 1M	$1.40 / 1M	$0.075 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	8.2K	1M	1M
Max output	N/A	N/A	N/A
Capabilities
Vision	No	No	Yes
Function Calling	No	Yes	Yes
JSON Mode	No	Yes	Yes
Streaming	No	Yes	Yes
Catalogue
Provider	Baidu	Z.AI	Z.AI
Category	chat	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	—	—
Description
Summary	—	GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.	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.