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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. Muse WonderMetaRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Nemotron 3.5 Lightning (Free)NVIDIARemove
  4. Transcribe 1 ProFish AudioRemove

4 is the maximum. Remove one to add another.

muse-wonder vs gemini-4-argon vs nemotron-3.5-lightning:free vs transcribe-1-pro
AttributeMuse Wondermuse-wonderGemini 4 Argongemini-4-argonNemotron 3.5 Lightning (Free)nemotron-3.5-lightning:freeTranscribe 1 Protranscribe-1-pro
Pricing
Input$4.00 / 1M$2.00 / 1M$0 / 1M— Not priced per input token
Output$20.00 / 1M$10.00 / 1M$0 / 1M— Not priced per output token
Cache Write (5m)$4.00 / 1M$2.00 / 1M—Not applicable
Cache Write (1h)$4.00 / 1M$2.00 / 1M—Not applicable
Cache Read$4.00 / 1M$2.00 / 1M$0 / 1MNot applicable
Web Search$0 / 1M$0 / 1M—$0 / 1M
Cache Write——$0 / 1M—
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderMetaGoogleNVIDIAFish Audio
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoFreePay As You Go
Released———2026-09-24
Description
SummaryMuse 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.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.NVIDIA Nemotron 3.5 Lightning is an open Mixture-of-Experts (MoE) model with 30B total parameters and 3B active per token, optimized for high-throughput agentic workloads and efficient inference. Its lightweight active compute and open design make it well suited for specialized agents, domain-specific customization, and scalable production deployments where speed, cost efficiency, and adaptability are key.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.