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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 1OpenAIRemove
  2. Muse WonderMetaRemove
  3. Nemotron 3.5 Super VL (Free)NVIDIARemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

whisper-1 vs muse-wonder vs nemotron-3.5-super-vl:free vs gemini-4-argon
AttributeWhisper 1whisper-1Muse Wondermuse-wonderNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGemini 4 Argongemini-4-argon
Pricing
Input$75.00 / 1M$4.00 / 1M$0 / 1M$2.00 / 1M
Output$75.00 / 1M$20.00 / 1M$0 / 1M$10.00 / 1M
Cache Write (5m)Not applicable$4.00 / 1M—$2.00 / 1M
Cache Write (1h)Not applicable$4.00 / 1M—$2.00 / 1M
Cache ReadNot applicable$4.00 / 1M$0 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M—$0 / 1M
Cache Write——$0 / 1M—
Context
Max contextN/A1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeYesYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderOpenAIMetaNVIDIAGoogle
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoFreePay As You Go
Released————
Description
SummaryWhisper (whisper-1) is OpenAI's open-source automatic speech recognition (ASR) model, designed for audio transcription and translation. It supports 50+ languages and processes audio files up to 25 MB, accepting formats such as mp3, mp4, wav, and webm. Optimized for reliable speech-to-text conversion across diverse audio inputs, Whisper is priced per minute of audio, billed to the nearest second, making it well suited for transcription, localization, and voice-driven applications.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.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.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.