Skip to content

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. Nemotron 3 Super (Free)NVIDIARemove
gpt-6.1-terra vs muse-spark-open vs nemotron-3-super-120b-a12b:free
AttributeGPT-6.1 Terragpt-6.1-terraMuse Spark Openmuse-spark-openNemotron 3 Super (Free)nemotron-3-super-120b-a12b:free
Pricing
Input$1.00 / 1M$1.25 / 1M$0 / 1M
Output$5.00 / 1M$4.25 / 1M$0 / 1M
Cache Write (5m)$1.00 / 1M$1.25 / 1M—
Cache Write (1h)$1.00 / 1M$1.25 / 1M—
Cache Read$1.00 / 1M$1.25 / 1M$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$0 / 1M
Context
Max context1M1M262.1K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIMetaNVIDIA
Categorychatchatchat
Charge typePay As You GoPay As You GoFree
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.NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid Mixture-of-Experts model designed for complex multi-agent and long-horizon reasoning workflows. It activates only 12B parameters per token, enabling high compute efficiency while maintaining strong accuracy on advanced tasks. Built on a hybrid Mamba–Transformer MoE architecture with multi-token prediction (MTP), the model delivers significantly higher token generation throughput than leading open models. It supports a 1M-token context window for long-context reasoning, cross-document analysis, and multi-step task planning. Trained with multi-environment reinforcement learning across diverse benchmarks—including AIME 2025, TerminalBench, and SWE-Bench Verified—Nemotron 3 Super achieves strong performance across reasoning and coding tasks. Released fully open with weights, datasets, and training recipes, it supports flexible customization and secure deployment from local workstations to cloud environments.