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| Attribute | Nemotron 3 Nano Omni (Free)nemotron-3-nano-omni-30b-a3b-reasoning:free | DeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017 |
|---|---|---|
| Pricing | ||
| Input | $0 / 1M | $0.10 / 1M |
| Output | $0 / 1M | $0.50 / 1M |
| Cache Write | $0 / 1M | — |
| Cache Read | $0 / 1M | $0.10 / 1M |
| Cache Write (5m) | — | $0.10 / 1M |
| Cache Write (1h) | — | $0.10 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | 256K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | NVIDIA | DeepSeek |
| Category | chat | chat |
| Charge type | Free | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | 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. | DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek’s cost-efficient Mixture-of-Experts (MoE) model, built on its innovative Causal Encoder-Decoder (CED) architecture. Featuring 552B total parameters with 8B activated for input and 16B for output, it combines efficient inference with native multimodal understanding through jointly trained text and visual representations. Optimized for coding, terminal and computer-use agents, and long-horizon workflows, the model introduces compressed KV caching that reduces cache memory usage to approximately one-quarter of the previous Flash generation. DeepSeek reports that it surpasses V4 Pro in performance, inference speed, and task completion time, making it well suited for cost-efficient autonomous agents, complex software engineering, and long-context analysis. |