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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. Claude Sonnet 4.6AnthropicRemove
  2. Muse Spark OpenMetaRemove
  3. Gemini 4 ArgonGoogleRemove
claude-sonnet-4-6 vs muse-spark-open vs gemini-4-argon
AttributeClaude Sonnet 4.6claude-sonnet-4-6Muse Spark Openmuse-spark-openGemini 4 Argongemini-4-argon
Pricing
Input$3.00 / 1M$1.25 / 1M$2.00 / 1M
Output$15.00 / 1M$4.25 / 1M$10.00 / 1M
Cache Write (5m)$3.75 / 1M$1.25 / 1M$2.00 / 1M
Cache Write (1h)$6.00 / 1M$1.25 / 1M$2.00 / 1M
Cache Read$0.30 / 1M$1.25 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicMetaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummarySonnet 4.6 is Anthropic's most capable Sonnet-class model, delivering frontier-level performance across coding, agent workflows, and professional knowledge tasks. It excels at iterative development, complex codebase navigation, and end-to-end project execution, supported by strong contextual understanding and persistent task handling. Beyond engineering tasks, Sonnet 4.6 produces polished documents and analyses while demonstrating reliable computer-use capabilities for web QA, workflow automation, and structured productivity workflows, making it well suited for both development and professional applications.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.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.