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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Hy4 previewTencentRemove
  2. Gemini 4 ArgonGoogleRemove
  3. GPT-5.6 Sol ProOpenAIRemove
hy4-preview vs gemini-4-argon vs gpt-5.6-sol-pro
AttributeHy4 previewhy4-previewGemini 4 Argongemini-4-argonGPT-5.6 Sol Progpt-5.6-sol-pro
Pricing
Input$0.834 / 1M$2.00 / 1M$5.00 / 1M
Output$2.50 / 1M$10.00 / 1M$30.00 / 1M
Cache Write (5m)$0.834 / 1M$2.00 / 1M$5.00 / 1M
Cache Write (1h)$0.834 / 1M$2.00 / 1M$5.00 / 1M
Cache Read$0.834 / 1M$2.00 / 1M$5.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderTencentGoogleOpenAI
Categorychatchatchat
Charge typePay 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.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.GPT-5.6 Sol Pro uses the same underlying model as GPT-5.6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning and more reliable execution, it is particularly well suited for advanced coding, long-horizon problem solving, and agentic workflows where accuracy and solution quality take priority over speed and cost.