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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.

  1. GLM-4Z.AIRemove
  2. Hy4 previewTencentRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3 FlashZ.AIRemove

4 is the maximum. Remove one to add another.

glm-4 vs hy4-preview vs muse-spark-1.3 vs glm-5.3-flash
AttributeGLM-4glm-4Hy4 previewhy4-previewMuse Spark 1.3muse-spark-1.3GLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.21 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Output$0.21 / 1M$2.50 / 1M$4.25 / 1M$0.25 / 1M
Cache Write (5m)$0.21 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Cache Write (1h)$0.21 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Cache Read$0.21 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context128K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderZ.AITencentMetaZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-4V-9B is the open-source multimodal model in Zhipu AI’s GLM-4 series. It supports high-resolution (1120×1120) bilingual Chinese–English dialogue across multiple turns, and performs strongly in perception, reasoning, OCR, and chart understanding. Across many multimodal benchmarks, it outperforms models such as GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max, and Claude 3 Opus.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.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.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.