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 | Nemotron 3.5 Super VLnemotron-3.5-super-vl | GPT-6.1 Terragpt-6.1-terra | Qwen3.5 Plus 2026-02-15qwen3.5-plus-02-15 |
|---|---|---|---|
| Pricing | |||
| Input | $0.10 / 1M | $1.00 / 1M | $0.26 / 1M |
| Output | $0.40 / 1M | $5.00 / 1M | $1.56 / 1M |
| Cache Write (5m) | $0.10 / 1M | $1.00 / 1M | $0.26 / 1M |
| Cache Write (1h) | $0.10 / 1M | $1.00 / 1M | $0.26 / 1M |
| Cache Read | $0.10 / 1M | $1.00 / 1M | $0.26 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1M | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | NVIDIA | OpenAI | Alibaba |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications. | 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. | Qwen3.5 Vision-Language Plus models are part of the native multimodal Qwen3.5 series, built on a hybrid architecture that combines linear attention mechanisms with sparse Mixture-of-Experts (MoE) designs to improve inference efficiency at scale. Across a wide range of evaluations, the series demonstrates performance comparable to leading state-of-the-art models. Compared with the Qwen3 generation, the 3.5 Plus models deliver significant improvements in both pure-text reasoning and multimodal understanding, making them well suited for applications that require strong performance across language, vision, and agent-based tasks. |