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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 3.7 FlashGoogleRemove
  2. GPT-4o TranscribeOpenAIRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

gemini-3.7-flash vs gpt-4o-transcribe vs muse-spark-1.3 vs glm-5.3
AttributeGemini 3.7 Flashgemini-3.7-flashGPT-4o Transcribegpt-4o-transcribeMuse Spark 1.3muse-spark-1.3GLM 5.3glm-5.3
Pricing
Input$0.375 / 1M$1.25 / 1M$1.25 / 1M$1.40 / 1M
Output$1.88 / 1M$0 / 1M$4.25 / 1M$4.40 / 1M
Cache Write (5m)$0.375 / 1MNot applicable$1.25 / 1M$1.40 / 1M
Cache Write (1h)$0.375 / 1MNot applicable$1.25 / 1M$1.40 / 1M
Cache Read$0.375 / 1MNot applicable$1.25 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M128K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesNoYesYes
JSON ModeYesYesYesYes
StreamingYesNoYesYes
Catalogue
ProviderGoogleOpenAIMetaZ.AI
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.GPT-4o Transcribe is OpenAI's high-quality speech-to-text model built on GPT-4o's audio capabilities. It delivers accurate transcription with strong language understanding, making it suitable for a wide range of audio processing tasks. Priced per token (input and output), it offers transparent, fine-grained billing, making it well suited for workflows that require scalable transcription, integration with LLM pipelines, and cost-aware processing.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.