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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Hy4 previewTencentRemove
  3. GPT-6 LunaOpenAIRemove
  4. Muse Spark OpenMetaRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs hy4-preview vs gpt-6-luna vs muse-spark-open
Attributemai-ds-r1:freeNot in the catalogueHy4 previewhy4-previewGPT-6 Lunagpt-6-lunaMuse Spark Openmuse-spark-open
Pricing
Input—$0.834 / 1M$0.10 / 1M$1.25 / 1M
Output—$2.50 / 1M$0.50 / 1M$4.25 / 1M
Cache Write (5m)—$0.834 / 1M$0.10 / 1M$1.25 / 1M
Cache Write (1h)—$0.834 / 1M$0.10 / 1M$1.25 / 1M
Cache Read—$0.834 / 1M$0.10 / 1M$1.25 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1M1.1M1M
Max output—N/AN/AN/A
Capabilities
Vision—YesYesYes
Function Calling—YesYesYes
JSON Mode—YesYesYes
Streaming—YesYesYes
Catalogue
Provider—TencentOpenAIMeta
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released————
Description
Summary—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.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.