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.

Kimi K3.1 ProMoonShot AI Remove
Muse WonderMeta Remove
Transcribe 1 ProFish Audio Remove
Qwen3.8 2.4T A95BAlibaba Remove

4 is the maximum. Remove one to add another.

kimi-k3.1-pro vs muse-wonder vs transcribe-1-pro vs qwen3.8-2.4t-a95b
Attribute	Kimi K3.1 Prokimi-k3.1-pro	Muse Wondermuse-wonder	Transcribe 1 Protranscribe-1-pro	Qwen3.8 2.4T A95Bqwen3.8-2.4t-a95b
Pricing
Input	$2.00 / 1M	$4.00 / 1M	— Not priced per input token	$1.80 / 1M
Output	$10.00 / 1M	$20.00 / 1M	— Not priced per output token	$5.40 / 1M
Cache Write (5m)	$2.00 / 1M	$4.00 / 1M	Not applicable	$1.80 / 1M
Cache Write (1h)	$2.00 / 1M	$4.00 / 1M	Not applicable	$1.80 / 1M
Cache Read	$2.00 / 1M	$4.00 / 1M	Not applicable	$1.80 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	1M	N/A	262K
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	Yes	No	Yes
Function Calling	Yes	Yes	No	Yes
JSON Mode	Yes	Yes	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	MoonShot AI	Meta	Fish Audio	Alibaba
Category	chat	chat	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	—	2026-09-24	—
Description
Summary	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.	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.	Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <\|speaker:0\|>. Billed per second of audio.	Qwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.