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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. GLM 5.3Z.AIRemove
  2. Claude Sonnet 5.5AnthropicRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Muse Spark OpenMetaRemove

4 is the maximum. Remove one to add another.

glm-5.3 vs claude-sonnet-5.5 vs gemini-4-argon vs muse-spark-open
AttributeGLM 5.3glm-5.3Claude Sonnet 5.5claude-sonnet-5.5Gemini 4 Argongemini-4-argonMuse Spark Openmuse-spark-open
Pricing
Input$1.40 / 1M$2.00 / 1M$2.00 / 1M$1.25 / 1M
Output$4.40 / 1M$10.00 / 1M$10.00 / 1M$4.25 / 1M
Cache Write (5m)$1.40 / 1M$2.50 / 1M$2.00 / 1M$1.25 / 1M
Cache Write (1h)$1.40 / 1M$4.00 / 1M$2.00 / 1M$1.25 / 1M
Cache Read$1.40 / 1M$0.10 / 1M$2.00 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderZ.AIAnthropicGoogleMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryGLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.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.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.