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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 Spark 1.3MetaRemove
  3. Gemini 3 Flash PreviewGoogleRemove
hy4-preview vs muse-spark-1.3 vs gemini-3-flash-preview
AttributeHy4 previewhy4-previewMuse Spark 1.3muse-spark-1.3Gemini 3 Flash Previewgemini-3-flash-preview
Pricing
Input$0.834 / 1M$1.25 / 1M$0.25 / 1M
Output$2.50 / 1M$4.25 / 1M$1.50 / 1M
Cache Write (5m)$0.834 / 1M$1.25 / 1M$0.25 / 1M
Cache Write (1h)$0.834 / 1M$1.25 / 1M$0.25 / 1M
Cache Read$0.834 / 1M$1.25 / 1M$0.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1.0M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderTencentMetaGoogle
Categorychatchatchat
Charge typePay 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.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 Flash Preview is a fast, cost-efficient reasoning model designed for agent workflows, multi-turn chat, and coding assistance. It offers near-Pro level reasoning and tool-use performance with significantly lower latency than larger Gemini models, making it ideal for interactive development and long-running agent loops. It improves on Gemini 2.5 Flash with stronger reasoning, multimodal understanding, and reliability. The model supports a 1M-token context window and multimodal inputs (text, images, audio, video, PDFs) with text outputs. It provides configurable reasoning levels, structured output formats, tool use, and automatic context caching—optimized for users seeking strong agentic reasoning without the cost or latency of full frontier-scale models.