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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. Gemini 3.8 FlashGoogleRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. GLM 5.3Z.AIRemove
  4. Whisper 1OpenAIRemove

4 is the maximum. Remove one to add another.

gemini-3.8-flash vs gpt-6-astra-pro vs glm-5.3 vs whisper-1
AttributeGemini 3.8 Flashgemini-3.8-flashGPT-6 Astra Progpt-6-astra-proGLM 5.3glm-5.3Whisper 1whisper-1
Pricing
Input$0.75 / 1M$10.00 / 1M$1.40 / 1M$75.00 / 1M
Output$3.75 / 1M$50.00 / 1M$4.40 / 1M$75.00 / 1M
Cache Write (5m)$0.75 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Cache Write (1h)$0.75 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Cache Read$0.75 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoNo
Function CallingYesYesYesNo
JSON ModeYesYesYesYes
StreamingYesYesYesNo
Catalogue
ProviderGoogleOpenAIZ.AIOpenAI
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 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.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.Whisper (whisper-1) is OpenAI's open-source automatic speech recognition (ASR) model, designed for audio transcription and translation. It supports 50+ languages and processes audio files up to 25 MB, accepting formats such as mp3, mp4, wav, and webm. Optimized for reliable speech-to-text conversion across diverse audio inputs, Whisper is priced per minute of audio, billed to the nearest second, making it well suited for transcription, localization, and voice-driven applications.