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 | Transcribe 1 Protranscribe-1-pro | DeepSeek V4 Pro 0813deepseek-v4-pro-0813 | Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free |
|---|---|---|---|
| Pricing | |||
| Input | — Not priced per input token | $0.435 / 1M | $0 / 1M |
| Output | — Not priced per output token | $0.87 / 1M | $0 / 1M |
| Cache Write (5m) | Not applicable | $0.435 / 1M | — |
| Cache Write (1h) | Not applicable | $0.435 / 1M | — |
| Cache Read | Not applicable | $0.435 / 1M | $0 / 1M |
| Web Search | $0 / 1M | $0 / 1M | — |
| Cache Write | — | — | $0 / 1M |
| Context | |||
| Max context | N/A | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | Yes | Yes |
| Function Calling | No | Yes | Yes |
| JSON Mode | No | Yes | Yes |
| Streaming | No | Yes | Yes |
| Catalogue | |||
| Provider | Fish Audio | DeepSeek | NVIDIA |
| Category | voice | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Free |
| Released | 2026-09-24 | — | — |
| Description | |||
| Summary | Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio. | DeepSeek V4 Pro 0813 is DeepSeek's large-scale Mixture-of-Experts (MoE) model and the general availability (GA) release of DeepSeek V4 Pro. It is designed for high-capability workloads requiring advanced reasoning, coding, and agentic task execution. As the production-ready V4 Pro release, it is well suited for complex software engineering, long-horizon agent workflows, and demanding reasoning tasks where reliability and model capability are critical. | 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. |