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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. DeepSeek V3 SearchDeepSeekRemove
  3. Qwen3.8 27BAlibabaRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

hy4-preview vs deepseek-v3-search vs qwen3.8-27b vs muse-spark-1.3
AttributeHy4 previewhy4-previewDeepSeek V3 Searchdeepseek-v3-searchQwen3.8 27Bqwen3.8-27bMuse Spark 1.3muse-spark-1.3
Pricing
Input$0.834 / 1M$2.80 / 1M$0.45 / 1M$1.25 / 1M
Output$2.50 / 1M$11.20 / 1M$3.20 / 1M$4.25 / 1M
Cache Write (5m)$0.834 / 1M$2.80 / 1M$0.45 / 1M$1.25 / 1M
Cache Write (1h)$0.834 / 1M$2.80 / 1M$0.45 / 1M$1.25 / 1M
Cache Read$0.834 / 1M$2.80 / 1M$0.45 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M163.8K262K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderTencentDeepSeekAlibabaMeta
Categorychatchatchatchat
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.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.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.