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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. GLM 5.3 FlashZ.AIRemove
  2. Transcribe 1 ProFish AudioRemove
  3. Muse Spark 1.3MetaRemove
glm-5.3-flash vs transcribe-1-pro vs muse-spark-1.3
AttributeGLM 5.3 Flashglm-5.3-flashTranscribe 1 Protranscribe-1-proMuse Spark 1.3muse-spark-1.3
Pricing
Input$0.075 / 1M— Not priced per input token$1.25 / 1M
Output$0.25 / 1M— Not priced per output token$4.25 / 1M
Cache Write (5m)$0.075 / 1MNot applicable$1.25 / 1M
Cache Write (1h)$0.075 / 1MNot applicable$1.25 / 1M
Cache Read$0.075 / 1MNot applicable$1.25 / 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
ProviderZ.AIFish AudioMeta
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-24—
Description
SummaryGLM-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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.