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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. Transcribe 1 ProFish AudioRemove
  2. Kimi K3.1 ProMoonShot AIRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

transcribe-1-pro vs kimi-k3.1-pro vs muse-spark-1.3 vs glm-5.3
AttributeTranscribe 1 Protranscribe-1-proKimi K3.1 Prokimi-k3.1-proMuse Spark 1.3muse-spark-1.3GLM 5.3glm-5.3
Pricing
Input— Not priced per input token$2.00 / 1M$1.25 / 1M$1.40 / 1M
Output— Not priced per output token$10.00 / 1M$4.25 / 1M$4.40 / 1M
Cache Write (5m)Not applicable$2.00 / 1M$1.25 / 1M$1.40 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$1.25 / 1M$1.40 / 1M
Cache ReadNot applicable$2.00 / 1M$1.25 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesNo
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderFish AudioMoonShot AIMetaZ.AI
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-24———
Description
SummaryFish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.