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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. DeepSeek V4 ProDeepSeekRemove
  2. Hy4 previewTencentRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3 FlashZ.AIRemove

4 is the maximum. Remove one to add another.

deepseek-v4-pro vs hy4-preview vs muse-spark-1.3 vs glm-5.3-flash
AttributeDeepSeek V4 Prodeepseek-v4-proHy4 previewhy4-previewMuse Spark 1.3muse-spark-1.3GLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.435 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Output$0.87 / 1M$2.50 / 1M$4.25 / 1M$0.25 / 1M
Cache Write (5m)$0.435 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Cache Write (1h)$0.435 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Cache Read$0.435 / 1M$0.834 / 1M$1.25 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.0M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderDeepSeekTencentMetaZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryDeepSeek V4 Pro is a large-scale Mixture-of-Experts (MoE) model with 1.6T total parameters and 49B activated per token, supporting a 1M-token context window for advanced reasoning and long-horizon workflows. It delivers strong performance across knowledge, mathematics, and software engineering tasks, making it suitable for complex, real-world applications. Built on a hybrid attention architecture for efficient long-context processing, the model supports configurable reasoning modes to balance speed and depth. It is well suited for full codebase analysis, multi-step automation, and large-scale information synthesis, where both capability and efficiency are essential.https://huggingface.co/deepseek-ai/DeepSeek-V4-ProTencent 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.