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.
| Attribute | GPT-6.1 Terragpt-6.1-terra | Nemotron 3 Nano Omni (Free)nemotron-3-nano-omni-30b-a3b-reasoning:free |
|---|---|---|
| Pricing | ||
| Input | $1.00 / 1M | $0 / 1M |
| Output | $5.00 / 1M | $0 / 1M |
| Cache Write (5m) | $1.00 / 1M | — |
| Cache Write (1h) | $1.00 / 1M | — |
| Cache Read | $1.00 / 1M | $0 / 1M |
| Web Search | $0 / 1M | — |
| Cache Write | — | $0 / 1M |
| Context | ||
| Max context | 1M | 256K |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | No | Yes |
| Catalogue | ||
| Provider | OpenAI | NVIDIA |
| Category | chat | chat |
| Charge type | Pay As You Go | Free |
| Released | — | — |
| Description | ||
| Summary | GPT-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. | NVIDIA Nemotron 3 Nano Omni is an open 30B-A3B multimodal model designed as a perception and context sub-agent for enterprise agent systems. It supports text, image, video, and audio inputs with text output, enabling unified multimodal reasoning within a single inference loop. Built on a hybrid MoE Transformer–Mamba architecture with Conv3D video layers and Efficient Video Sampling (EVS), it delivers significantly improved efficiency for video reasoning—achieving ~2× higher throughput and 2.5× lower compute compared to separate pipelines. With up to 300K context length and extended thinking support, it is well suited for scalable, multimodal agent workflows. |