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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. Gemini 4 ArgonGoogleRemove
  3. Transcribe 1 ProFish AudioRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

kimi-k3.1-pro vs gemini-4-argon vs transcribe-1-pro vs muse-wonder
AttributeKimi K3.1 Prokimi-k3.1-proGemini 4 Argongemini-4-argonTranscribe 1 Protranscribe-1-proMuse Wondermuse-wonder
Pricing
Input$2.00 / 1M$2.00 / 1M— Not priced per input token$4.00 / 1M
Output$10.00 / 1M$10.00 / 1M— Not priced per output token$20.00 / 1M
Cache Write (5m)$2.00 / 1M$2.00 / 1MNot applicable$4.00 / 1M
Cache Write (1h)$2.00 / 1M$2.00 / 1MNot applicable$4.00 / 1M
Cache Read$2.00 / 1M$2.00 / 1MNot applicable$4.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1MN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderMoonShot AIGoogleFish AudioMeta
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-24—
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.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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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.