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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 4.7 FlashZ.AIRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

glm-4.7-flash vs gemini-3.8-flash vs muse-spark-1.3 vs glm-5.3
AttributeGLM 4.7 Flashglm-4.7-flashGemini 3.8 Flashgemini-3.8-flashMuse Spark 1.3muse-spark-1.3GLM 5.3glm-5.3
Pricing
Input$0.06 / 1M$0.75 / 1M$1.25 / 1M$1.40 / 1M
Output$0.40 / 1M$3.75 / 1M$4.25 / 1M$4.40 / 1M
Cache Write (5m)$0.06 / 1M$0.75 / 1M$1.25 / 1M$1.40 / 1M
Cache Write (1h)$0.06 / 1M$0.75 / 1M$1.25 / 1M$1.40 / 1M
Cache Read$0.06 / 1M$0.75 / 1M$1.25 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context200K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesNo
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderZ.AIGoogleMetaZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-4.7-Flash is a state-of-the-art 30B-class model designed to strike a strong balance between performance and efficiency. It is specifically optimized for agentic coding scenarios, with enhanced capabilities in code generation, long-horizon task planning, and tool-based collaboration. Among open-source models of comparable size, GLM-4.7-Flash has achieved leading results on multiple public benchmark leaderboards, establishing itself as a competitive and practical choice for advanced developer and agent 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.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.GLM-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.