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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 Spark OpenMetaRemove
  3. GPT-4o Audio PreviewOpenAIRemove
gpt-6.1-terra vs muse-spark-open vs gpt-4o-audio-preview
AttributeGPT-6.1 Terragpt-6.1-terraMuse Spark Openmuse-spark-openGPT-4o Audio Previewgpt-4o-audio-preview
Pricing
Input$1.00 / 1M$1.25 / 1M$0.875 / 1M
Output$5.00 / 1M$4.25 / 1M$3.50 / 1M
Cache Write (5m)$1.00 / 1M$1.25 / 1MNot applicable
Cache Write (1h)$1.00 / 1M$1.25 / 1MNot applicable
Cache Read$1.00 / 1M$1.25 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M128K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingNoYesYes
Catalogue
ProviderOpenAIMetaOpenAI
Categorychatchatvoice
Charge typePay 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 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.gpt-4o-audio-preview adds support for audio inputs, allowing the model to understand nuances in audio recordings and enrich responses. It currently does not generate audio outputs, and audio input is billed per million audio tokens.