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. Perceptron Mk1.5PerceptronRemove
  2. Nemotron 3.5 LightningNVIDIARemove
  3. Gemini 4 ArgonGoogleRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs nemotron-3.5-lightning vs gemini-4-argon vs muse-wonder
AttributePerceptron Mk1.5perceptron-mk1.5Nemotron 3.5 Lightningnemotron-3.5-lightningGemini 4 Argongemini-4-argonMuse Wondermuse-wonder
Pricing
Input$0.15 / 1M— Not priced per input token$2.00 / 1M$4.00 / 1M
Output$1.50 / 1M— Not priced per output token$10.00 / 1M$20.00 / 1M
Cache Write (5m)$0.15 / 1M$0.00 / 1M$2.00 / 1M$4.00 / 1M
Cache Write (1h)$0.15 / 1M$0.00 / 1M$2.00 / 1M$4.00 / 1M
Cache Read$0.15 / 1M$0.00 / 1M$2.00 / 1M$4.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context36.9K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderPerceptronNVIDIAGoogleMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-25———
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.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.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.