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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. Hy4 previewTencentRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

gpt-5.6-sol-pro vs hy4-preview vs perceptron-mk1.5 vs muse-wonder
AttributeGPT-5.6 Sol Progpt-5.6-sol-proHy4 previewhy4-previewPerceptron Mk1.5perceptron-mk1.5Muse Wondermuse-wonder
Pricing
Input$5.00 / 1M$0.834 / 1M$0.15 / 1M$4.00 / 1M
Output$30.00 / 1M$2.50 / 1M$1.50 / 1M$20.00 / 1M
Cache Write (5m)$5.00 / 1M$0.834 / 1M$0.15 / 1M$4.00 / 1M
Cache Write (1h)$5.00 / 1M$0.834 / 1M$0.15 / 1M$4.00 / 1M
Cache Read$5.00 / 1M$0.834 / 1M$0.15 / 1M$4.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAITencentPerceptronMeta
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.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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.