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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. mai-ds-r1:freeNot in the catalogueRemove
  3. Transcribe 1 ProFish AudioRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

hy4-preview vs mai-ds-r1:free vs transcribe-1-pro vs gemini-4-argon
AttributeHy4 previewhy4-previewmai-ds-r1:freeNot in the catalogueTranscribe 1 Protranscribe-1-proGemini 4 Argongemini-4-argon
Pricing
Input$0.834 / 1M—— Not priced per input token$2.00 / 1M
Output$2.50 / 1M—— Not priced per output token$10.00 / 1M
Cache Write (5m)$0.834 / 1M—Not applicable$2.00 / 1M
Cache Write (1h)$0.834 / 1M—Not applicable$2.00 / 1M
Cache Read$0.834 / 1M—Not applicable$2.00 / 1M
Web Search$0 / 1M—$0 / 1M$0 / 1M
Context
Max context1M—N/A1M
Max outputN/A—N/AN/A
Capabilities
VisionYes—NoYes
Function CallingYes—NoYes
JSON ModeYes—NoYes
StreamingYes—NoYes
Catalogue
ProviderTencent—Fish AudioGoogle
Categorychat—voicechat
Charge typePay As You Go—Pay As You GoPay As You Go
Released——2026-09-24—
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.—Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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.