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. Whisper Large V3OpenAIRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. DeepSeek V4.1 Flash 1017DeepSeekRemove
whisper-large-v3 vs nemotron-3.5-super-vl:free vs deepseek-v4.1-flash-1017
AttributeWhisper Large V3whisper-large-v3Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeDeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017
Pricing
Input$9.25 / 1M$0 / 1M$0.20 / 1M
Output— Not priced per output token$0 / 1M$0.80 / 1M
Cache Write (5m)Not applicable—$0.20 / 1M
Cache Write (1h)Not applicable—$0.20 / 1M
Cache ReadNot applicable$0 / 1M$0.20 / 1M
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeYesYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAINVIDIADeepSeek
Categoryvoicechatchat
Charge typePay As You GoFreePay As You Go
Released———
Description
SummaryWhisper Large V3 is OpenAI's advanced open-source automatic speech recognition (ASR) model, supporting both audio transcription and translation across 99+ languages. It accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg, and delivers strong performance in noisy, real-world conditions. With 1.55B parameters and a low 10.3% word error rate, it provides accurate, multilingual transcription with support for word- and segment-level timestamps, making it well suited for high-quality, noise-robust speech processing applications.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.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.