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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. Grok 4.20 Multi-Agent BetaxAIRemove
  2. Muse Spark 1.3MetaRemove
  3. Gemini 3.8 FlashGoogleRemove
grok-4.20-multi-agent-beta vs muse-spark-1.3 vs gemini-3.8-flash
AttributeGrok 4.20 Multi-Agent Betagrok-4.20-multi-agent-betaMuse Spark 1.3muse-spark-1.3Gemini 3.8 Flashgemini-3.8-flash
Pricing
Input$2.00 / 1M$1.25 / 1M$0.75 / 1M
Output$6.00 / 1M$4.25 / 1M$3.75 / 1M
Cache Write (5m)$2.00 / 1M$1.25 / 1M$0.75 / 1M
Cache Write (1h)$2.00 / 1M$1.25 / 1M$0.75 / 1M
Cache Read$2.00 / 1M$1.25 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context2M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderxAIMetaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGrok 4.20 Multi-Agent Beta is a specialized variant of xAI's Grok 4.20 designed for collaborative, agent-based workflows. It enables multiple agents to operate in parallel, coordinating tool use and information synthesis to handle complex tasks. Optimized for deep research and multi-step problem solving, the model supports parallel reasoning, coordinated execution, and structured knowledge synthesis across large and complex 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 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.