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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 3.8 FlashGoogleRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Nemotron 3.5 Super VLNVIDIARemove

4 is the maximum. Remove one to add another.

muse-wonder vs gemini-3.8-flash vs perceptron-mk1.5 vs nemotron-3.5-super-vl
AttributeMuse Wondermuse-wonderGemini 3.8 Flashgemini-3.8-flashPerceptron Mk1.5perceptron-mk1.5Nemotron 3.5 Super VLnemotron-3.5-super-vl
Pricing
Input$4.00 / 1M$0.75 / 1M$0.15 / 1M$0.10 / 1M
Output$20.00 / 1M$3.75 / 1M$1.50 / 1M$0.40 / 1M
Cache Write (5m)$4.00 / 1M$0.75 / 1M$0.15 / 1M$0.10 / 1M
Cache Write (1h)$4.00 / 1M$0.75 / 1M$0.15 / 1M$0.10 / 1M
Cache Read$4.00 / 1M$0.75 / 1M$0.15 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesYesYes
Catalogue
ProviderMetaGooglePerceptronNVIDIA
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-25—
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 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.