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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. ERNIE Speed 128KBaiduRemove
  2. Hy4 previewTencentRemove
  3. Qwen3.8 27BAlibabaRemove
  4. GLM 5.3 FlashZ.AIRemove

4 is the maximum. Remove one to add another.

ERNIE-Speed-128K vs hy4-preview vs qwen3.8-27b vs glm-5.3-flash
AttributeERNIE Speed 128KERNIE-Speed-128KHy4 previewhy4-previewQwen3.8 27Bqwen3.8-27bGLM 5.3 Flashglm-5.3-flash
Pricing
Input$1.46 / 1M$0.834 / 1M$0.45 / 1M$0.075 / 1M
Output$2.92 / 1M$2.50 / 1M$3.20 / 1M$0.25 / 1M
Cache Write (5m)$1.457 / 1M$0.834 / 1M$0.45 / 1M$0.075 / 1M
Cache Write (1h)$1.457 / 1M$0.834 / 1M$0.45 / 1M$0.075 / 1M
Cache Read$1.457 / 1M$0.834 / 1M$0.45 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context131.1K1M262K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderBaiduTencentAlibabaZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryTencent 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.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.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.