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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Whisper Large V3 TurboOpenAIRemove
  2. Gemini 3.7 FlashGoogleRemove
  3. GLM 5.3 FlashZ.AIRemove
whisper-large-v3-turbo vs gemini-3.7-flash vs glm-5.3-flash
AttributeWhisper Large V3 Turbowhisper-large-v3-turboGemini 3.7 Flashgemini-3.7-flashGLM 5.3 Flashglm-5.3-flash
Pricing
Input$3.33 / 1M$0.375 / 1M$0.075 / 1M
Output$0 / 1M$1.88 / 1M$0.25 / 1M
Cache Write (5m)Not applicable$0.375 / 1M$0.075 / 1M
Cache Write (1h)Not applicable$0.375 / 1M$0.075 / 1M
Cache ReadNot applicable$0.375 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIGoogleZ.AI
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryWhisper 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.Gemini 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-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.