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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. GPT-6.1 TerraOpenAIRemove
  2. Muse WonderMetaRemove
  3. GPT-4o TranscribeOpenAIRemove
  4. Muse Spark OpenMetaRemove

4 is the maximum. Remove one to add another.

gpt-6.1-terra vs muse-wonder vs gpt-4o-transcribe vs muse-spark-open
AttributeGPT-6.1 Terragpt-6.1-terraMuse Wondermuse-wonderGPT-4o Transcribegpt-4o-transcribeMuse Spark Openmuse-spark-open
Pricing
Input$1.00 / 1M$4.00 / 1M$1.25 / 1M$1.25 / 1M
Output$5.00 / 1M$20.00 / 1M— Not priced per output token$4.25 / 1M
Cache Write (5m)$1.00 / 1M$4.00 / 1MNot applicable$1.25 / 1M
Cache Write (1h)$1.00 / 1M$4.00 / 1MNot applicable$1.25 / 1M
Cache Read$1.00 / 1M$4.00 / 1MNot applicable$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M128K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesYesYes
StreamingNoYesNoYes
Catalogue
ProviderOpenAIMetaOpenAIMeta
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryGPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.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 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.