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. Gemini 3.7 FlashGoogleRemove
  2. GLM 5.3Z.AIRemove
  3. GPT-6 Astra ProOpenAIRemove
gemini-3.7-flash vs glm-5.3 vs gpt-6-astra-pro
AttributeGemini 3.7 Flashgemini-3.7-flashGLM 5.3glm-5.3GPT-6 Astra Progpt-6-astra-pro
Pricing
Input$0.375 / 1M$1.40 / 1M$10.00 / 1M
Output$1.88 / 1M$4.40 / 1M$50.00 / 1M
Cache Write (5m)$0.375 / 1M$1.40 / 1M$10.00 / 1M
Cache Write (1h)$0.375 / 1M$1.40 / 1M$10.00 / 1M
Cache Read$0.375 / 1M$1.40 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleZ.AIOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.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.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.