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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 3.5 TranscribeGoogleRemove
  2. GPT-5.6 Sol ProOpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.5-transcribe vs gpt-5.6-sol-pro vs glm-5.3-flash
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGPT-5.6 Sol Progpt-5.6-sol-proGLM 5.3 Flashglm-5.3-flash
Pricing
Input— Not priced per input token$5.00 / 1M$0.075 / 1M
Output— Not priced per output token$30.00 / 1M$0.25 / 1M
Cache Write (5m)Not applicable$5.00 / 1M$0.075 / 1M
Cache Write (1h)Not applicable$5.00 / 1M$0.075 / 1M
Cache ReadNot applicable$5.00 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context98.3K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleOpenAIZ.AI
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.GPT-5.6 Sol Pro uses the same underlying model as GPT-5.6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning and more reliable execution, it is particularly well suited for advanced coding, long-horizon problem solving, and agentic workflows where accuracy and solution quality take priority over speed and cost.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.