Skip to content

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 4.6 (Thinking)Z.AIRemove
  2. Muse Spark 1.3MetaRemove
  3. GPT-6 AstraOpenAIRemove
glm-4.6-thinking vs muse-spark-1.3 vs gpt-6-astra
AttributeGLM 4.6 (Thinking)glm-4.6-thinkingMuse Spark 1.3muse-spark-1.3GPT-6 Astragpt-6-astra
Pricing
Input$0.40 / 1M$1.25 / 1M$10.00 / 1M
Output$1.50 / 1M$4.25 / 1M$50.00 / 1M
Cache Write (5m)$0.40 / 1M$1.25 / 1M$10.00 / 1M
Cache Write (1h)$0.40 / 1M$1.25 / 1M$10.00 / 1M
Cache Read$0.40 / 1M$1.25 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context202.8K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIMetaOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-4.6 improves on GLM-4.5 with a larger 200K context window, stronger coding performance (including better real-world agent tools like Claude Code and Cline), and clearer gains in reasoning with built-in tool use. It delivers more capable agent behavior, integrates better into agent frameworks, and produces more natural, readable writing — especially in role-playing scenarios.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.GPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.