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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. Muse WonderMetaRemove
  3. Qwen3.5 397B A17BAlibabaRemove
  4. Muse Spark OpenMetaRemove

4 is the maximum. Remove one to add another.

kimi-k3.1-pro vs muse-wonder vs qwen3.5-397b-a17b vs muse-spark-open
AttributeKimi K3.1 Prokimi-k3.1-proMuse Wondermuse-wonderQwen3.5 397B A17Bqwen3.5-397b-a17bMuse Spark Openmuse-spark-open
Pricing
Input$2.00 / 1M$4.00 / 1M$0.55 / 1M$1.25 / 1M
Output$10.00 / 1M$20.00 / 1M$3.50 / 1M$4.25 / 1M
Cache Write (5m)$2.00 / 1M$4.00 / 1M$0.55 / 1M$1.25 / 1M
Cache Write (1h)$2.00 / 1M$4.00 / 1M$0.55 / 1M$1.25 / 1M
Cache Read$2.00 / 1M$4.00 / 1M$0.55 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M256K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderMoonShot AIMetaAlibabaMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay 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.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.Qwen3.5-397B-A17B is a native vision-language model built on a hybrid architecture that combines linear attention mechanisms with a sparse Mixture-of-Experts (MoE) design to achieve higher inference efficiency at large scale. It delivers state-of-the-art performance across a broad range of tasks, including language understanding, logical reasoning, code generation, agent-based workflows, image and video understanding, and GUI interaction. With strong coding and agent capabilities, Qwen3.5-397B-A17B demonstrates robust generalization across diverse multimodal and agentic scenarios, making it well suited for advanced applications that require integrated reasoning across text, vision, and interactive environments.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.