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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. Mistral Embed 2312Mistral AIRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. GLM 5.3Z.AIRemove
mistral-embed-2312 vs gpt-6-astra-pro vs glm-5.3
AttributeMistral Embed 2312mistral-embed-2312GPT-6 Astra Progpt-6-astra-proGLM 5.3glm-5.3
Pricing
Input$0.125 / 1M$10.00 / 1M$1.40 / 1M
Output$0 / 1M$50.00 / 1M$4.40 / 1M
Cache Write (5m)$0.125 / 1M$10.00 / 1M$1.40 / 1M
Cache Write (1h)$0.125 / 1M$10.00 / 1M$1.40 / 1M
Cache Read$0.125 / 1M$10.00 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context8.2K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesNo
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderMistral AIOpenAIZ.AI
Categoryembeddingchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryMistral Embed is Mistral AI's text embedding model, built for semantic search and RAG workflows. It generates 1024-dimensional vectors that capture meaningful relationships between pieces of text.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.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.