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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 5.3 FlashZ.AIRemove
  2. Claude Sonnet 5.5AnthropicRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Hy4 previewTencentRemove

4 is the maximum. Remove one to add another.

glm-5.3-flash vs claude-sonnet-5.5 vs gemini-4-argon vs hy4-preview
AttributeGLM 5.3 Flashglm-5.3-flashClaude Sonnet 5.5claude-sonnet-5.5Gemini 4 Argongemini-4-argonHy4 previewhy4-preview
Pricing
Input$0.075 / 1M$2.00 / 1M$2.00 / 1M$0.834 / 1M
Output$0.25 / 1M$10.00 / 1M$10.00 / 1M$2.50 / 1M
Cache Write (5m)$0.075 / 1M$2.50 / 1M$2.00 / 1M$0.834 / 1M
Cache Write (1h)$0.075 / 1M$4.00 / 1M$2.00 / 1M$0.834 / 1M
Cache Read$0.075 / 1M$0.10 / 1M$2.00 / 1M$0.834 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderZ.AIAnthropicGoogleTencent
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryGLM-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.Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.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.