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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. Qwen2.5 VL 3B InstructAlibabaRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
  4. Hy4 previewTencentRemove

4 is the maximum. Remove one to add another.

qwen2.5-vl-3b-instruct vs glm-5.3 vs muse-spark-1.3 vs hy4-preview
AttributeQwen2.5 VL 3B Instructqwen2.5-vl-3b-instructGLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3Hy4 previewhy4-preview
Pricing
Input$0 / 1M$1.40 / 1M$1.25 / 1M$0.834 / 1M
Output$0 / 1M$4.40 / 1M$4.25 / 1M$2.50 / 1M
Cache Write (5m)$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.834 / 1M
Cache Write (1h)$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.834 / 1M
Cache Read$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.834 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context64K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoNoYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderAlibabaZ.AIMetaTencent
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-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.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.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.