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

4 is the maximum. Remove one to add another.

claude-sonnet-5.5 vs hy4-preview vs gemini-4-argon vs glm-5.3-flash
AttributeClaude Sonnet 5.5claude-sonnet-5.5Hy4 previewhy4-previewGemini 4 Argongemini-4-argonGLM 5.3 Flashglm-5.3-flash
Pricing
Input$2.00 / 1M$0.834 / 1M$2.00 / 1M$0.075 / 1M
Output$10.00 / 1M$2.50 / 1M$10.00 / 1M$0.25 / 1M
Cache Write (5m)$2.50 / 1M$0.834 / 1M$2.00 / 1M$0.075 / 1M
Cache Write (1h)$4.00 / 1M$0.834 / 1M$2.00 / 1M$0.075 / 1M
Cache Read$0.10 / 1M$0.834 / 1M$2.00 / 1M$0.075 / 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
ProviderAnthropicTencentGoogleZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryClaude 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.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.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.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.