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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. Muse Spark OpenMetaRemove
  2. Transcribe 1 ProFish AudioRemove
  3. GLM 5Z.AIRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs transcribe-1-pro vs glm-5 vs gemini-4-argon
AttributeMuse Spark Openmuse-spark-openTranscribe 1 Protranscribe-1-proGLM 5glm-5Gemini 4 Argongemini-4-argon
Pricing
Input$1.25 / 1M— Not priced per input token$0.60 / 1M$2.00 / 1M
Output$4.25 / 1M— Not priced per output token$2.20 / 1M$10.00 / 1M
Cache Write (5m)$1.25 / 1MNot applicable$0.60 / 1M$2.00 / 1M
Cache Write (1h)$1.25 / 1MNot applicable$0.60 / 1M$2.00 / 1M
Cache Read$1.25 / 1MNot applicable$0.60 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1MN/A202.8K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderMetaFish AudioZ.AIGoogle
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-24——
Description
SummaryMuse 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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.GLM-5 is Z.AI's flagship open-source foundation model, engineered for complex systems design and long-horizon agent workflows. Built with expert developers in mind, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With strong agentic planning, deep backend reasoning, and iterative self-correction capabilities, GLM-5 extends beyond traditional code generation to support full-system construction and autonomous execution, making it well suited for advanced engineering and agent-driven development environments.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.