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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. Gemini 3.5 TranscribeGoogleRemove
  2. Muse WonderMetaRemove
  3. Hy4 previewTencentRemove
  4. mai-ds-r1:freeNot in the catalogueRemove

4 is the maximum. Remove one to add another.

gemini-3.5-transcribe vs muse-wonder vs hy4-preview vs mai-ds-r1:free
AttributeGemini 3.5 Transcribegemini-3.5-transcribeMuse Wondermuse-wonderHy4 previewhy4-previewmai-ds-r1:freeNot in the catalogue
Pricing
Input— Not priced per input token$4.00 / 1M$0.834 / 1M—
Output— Not priced per output token$20.00 / 1M$2.50 / 1M—
Cache Write (5m)Not applicable$4.00 / 1M$0.834 / 1M—
Cache Write (1h)Not applicable$4.00 / 1M$0.834 / 1M—
Cache ReadNot applicable$4.00 / 1M$0.834 / 1M—
Web Search$0 / 1M$0 / 1M$0 / 1M—
Context
Max context98.3K1M1M—
Max outputN/AN/AN/A—
Capabilities
VisionYesYesYes—
Function CallingYesYesYes—
JSON ModeNoYesYes—
StreamingNoYesYes—
Catalogue
ProviderGoogleMetaTencent—
Categoryvoicechatchat—
Charge typePay As You GoPay As You GoPay As You Go—
Released2026-09-25———
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output 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.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.—