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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. Gemini 3.5 TranscribeGoogleRemove
  2. Muse Spark OpenMetaRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.5-transcribe vs muse-spark-open vs glm-5.3-flash
AttributeGemini 3.5 Transcribegemini-3.5-transcribeMuse Spark Openmuse-spark-openGLM 5.3 Flashglm-5.3-flash
Pricing
Input— Not priced per input token$1.25 / 1M$0.075 / 1M
Output— Not priced per output token$4.25 / 1M$0.25 / 1M
Cache Write (5m)Not applicable$1.25 / 1M$0.075 / 1M
Cache Write (1h)Not applicable$1.25 / 1M$0.075 / 1M
Cache ReadNot applicable$1.25 / 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
ProviderGoogleMetaZ.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.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.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.