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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. Hy4 previewTencentRemove
  2. Muse WonderMetaRemove
  3. mai-ds-r1:freeNot in the catalogueRemove
  4. GPT-6.1 SolOpenAIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs muse-wonder vs mai-ds-r1:free vs gpt-6.1-sol
AttributeHy4 previewhy4-previewMuse Wondermuse-wondermai-ds-r1:freeNot in the catalogueGPT-6.1 Solgpt-6.1-sol
Pricing
Input$0.834 / 1M$4.00 / 1M—$2.00 / 1M
Output$2.50 / 1M$20.00 / 1M—$10.00 / 1M
Cache Write (5m)$0.834 / 1M$4.00 / 1M—$2.00 / 1M
Cache Write (1h)$0.834 / 1M$4.00 / 1M—$2.00 / 1M
Cache Read$0.834 / 1M$4.00 / 1M—$2.00 / 1M
Web Search$0 / 1M$0 / 1M—$0 / 1M
Context
Max context1M1M—1M
Max outputN/AN/A—N/A
Capabilities
VisionYesYes—Yes
Function CallingYesYes—Yes
JSON ModeYesYes—Yes
StreamingYesYes—Yes
Catalogue
ProviderTencentMeta—OpenAI
Categorychatchat—chat
Charge typePay As You GoPay As You Go—Pay 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.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.—GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.