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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. Kimi K3.1 ProMoonShot AIRemove
  2. GPT Image 2OpenAIRemove
  3. Muse WonderMetaRemove
kimi-k3.1-pro vs gpt-image-2 vs muse-wonder
AttributeKimi K3.1 Prokimi-k3.1-proGPT Image 2gpt-image-2Muse Wondermuse-wonder
Pricing
Input$2.00 / 1M—$4.00 / 1M
Output$10.00 / 1M—$20.00 / 1M
Cache Write (5m)$2.00 / 1MNot applicable$4.00 / 1M
Cache Write (1h)$2.00 / 1MNot applicable$4.00 / 1M
Cache Read$2.00 / 1MNot applicable$4.00 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.04 / request—
Billing—Pay Per Request—
Context
Max context1M272K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderMoonShot AIOpenAIMeta
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released———
Description
SummaryKimi 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.GPT Image 2 combines OpenAI's GPT-5.4 with advanced image generation capabilities from GPT Image 2, enabling fully integrated multimodal workflows. It allows users to seamlessly transition between reasoning, coding, and visual generation within a single interaction, making it well suited for creative, development, and agent-driven applications that require both intelligence and visual output.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.