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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. GPT-5.6 Sol ProOpenAIRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. Hy4 previewTencentRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

gpt-5.6-sol-pro vs perceptron-mk1.5 vs hy4-preview vs gemini-4-argon
AttributeGPT-5.6 Sol Progpt-5.6-sol-proPerceptron Mk1.5perceptron-mk1.5Hy4 previewhy4-previewGemini 4 Argongemini-4-argon
Pricing
Input$5.00 / 1M$0.15 / 1M$0.834 / 1M$2.00 / 1M
Output$30.00 / 1M$1.50 / 1M$2.50 / 1M$10.00 / 1M
Cache Write (5m)$5.00 / 1M$0.15 / 1M$0.834 / 1M$2.00 / 1M
Cache Write (1h)$5.00 / 1M$0.15 / 1M$0.834 / 1M$2.00 / 1M
Cache Read$5.00 / 1M$0.15 / 1M$0.834 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M36.9K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIPerceptronTencentGoogle
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-25——
Description
SummaryGPT-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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.