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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. Qwen3.8 27BAlibabaRemove
  2. Moonlight 16B A3B InstructMoonshot AIRemove
  3. Muse Spark 1.3MetaRemove
qwen3.8-27b vs moonlight-16b-a3b-instruct vs muse-spark-1.3
AttributeQwen3.8 27Bqwen3.8-27bMoonlight 16B A3B Instructmoonlight-16b-a3b-instructMuse Spark 1.3muse-spark-1.3
Pricing
Input$0.45 / 1M$0 / 1M$1.25 / 1M
Output$3.20 / 1M$0 / 1M$4.25 / 1M
Cache Write (5m)$0.45 / 1M$0.00 / 1M$1.25 / 1M
Cache Write (1h)$0.45 / 1M$0.00 / 1M$1.25 / 1M
Cache Read$0.45 / 1M$0.00 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context262K8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderAlibabaMoonshot AIMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryQwen3.8 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.