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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. GPT-4o TranscribeOpenAIRemove
  3. Muse Spark 1.3MetaRemove
  4. Gemini 3.7 FlashGoogleRemove

4 is the maximum. Remove one to add another.

hy4-preview vs gpt-4o-transcribe vs muse-spark-1.3 vs gemini-3.7-flash
AttributeHy4 previewhy4-previewGPT-4o Transcribegpt-4o-transcribeMuse Spark 1.3muse-spark-1.3Gemini 3.7 Flashgemini-3.7-flash
Pricing
Input$0.834 / 1M$1.25 / 1M$1.25 / 1M$0.375 / 1M
Output$2.50 / 1M$0 / 1M$4.25 / 1M$1.88 / 1M
Cache Write (5m)$0.834 / 1MNot applicable$1.25 / 1M$0.375 / 1M
Cache Write (1h)$0.834 / 1MNot applicable$1.25 / 1M$0.375 / 1M
Cache Read$0.834 / 1MNot applicable$1.25 / 1M$0.375 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M128K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesYesYesYes
StreamingYesNoYesYes
Catalogue
ProviderTencentOpenAIMetaGoogle
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay 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.GPT-4o Transcribe is OpenAI's high-quality speech-to-text model built on GPT-4o's audio capabilities. It delivers accurate transcription with strong language understanding, making it suitable for a wide range of audio processing tasks. Priced per token (input and output), it offers transparent, fine-grained billing, making it well suited for workflows that require scalable transcription, integration with LLM pipelines, and cost-aware processing.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.