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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. Whisper Large V3 TurboOpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.8-flash vs whisper-large-v3-turbo vs glm-5.3-flash
AttributeGemini 3.8 Flashgemini-3.8-flashWhisper Large V3 Turbowhisper-large-v3-turboGLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.75 / 1M$3.33 / 1M$0.075 / 1M
Output$3.75 / 1M$0 / 1M$0.25 / 1M
Cache Write (5m)$0.75 / 1MNot applicable$0.075 / 1M
Cache Write (1h)$0.75 / 1MNot applicable$0.075 / 1M
Cache Read$0.75 / 1MNot applicable$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1MN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderGoogleOpenAIZ.AI
Categorychatvoicechat
Charge typePay 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.Whisper Large V3 Turbo is an optimized version of OpenAI's Whisper Large V3 speech recognition model, designed for high-speed and cost-efficient transcription. It supports 99+ languages and accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg. With a ~12% word error rate and real-time speed factors up to 216×, it delivers fast, scalable performance for latency-sensitive and high-throughput transcription workloads, making it ideal for real-time and large-scale speech processing applications.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.