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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. Nemotron 3.5 Super VLNVIDIARemove
  3. Kimi K2Moonshot AIRemove
  4. Kimi K3.1 ProMoonShot AIRemove

4 is the maximum. Remove one to add another.

muse-wonder vs nemotron-3.5-super-vl vs kimi-k2 vs kimi-k3.1-pro
AttributeMuse Wondermuse-wonderNemotron 3.5 Super VLnemotron-3.5-super-vlKimi K2kimi-k2Kimi K3.1 Prokimi-k3.1-pro
Pricing
Input$4.00 / 1M$0.10 / 1M$0.34 / 1M$2.00 / 1M
Output$20.00 / 1M$0.40 / 1M$1.50 / 1M$10.00 / 1M
Cache Write (5m)$4.00 / 1M$0.10 / 1M$0.34 / 1M$2.00 / 1M
Cache Write (1h)$4.00 / 1M$0.10 / 1M$0.34 / 1M$2.00 / 1M
Cache Read$4.00 / 1M$0.10 / 1M$0.34 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M63K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderMetaNVIDIAMoonshot AIMoonShot AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
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.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.Kimi K2-Instruct-0905 is the newest and strongest Kimi K2 model — a trillion-parameter MoE system with 32B active parameters. It delivers major gains in agentic coding, better frontend development results, and an expanded 256K context window for longer tasks.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.