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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. Qwen3 MaxAlibabaRemove
  3. Gemini 4 ArgonGoogleRemove
kimi-k3.1-pro vs qwen3-max vs gemini-4-argon
AttributeKimi K3.1 Prokimi-k3.1-proQwen3 Maxqwen3-maxGemini 4 Argongemini-4-argon
Pricing
Input$2.00 / 1M$1.20 / 1M$2.00 / 1M
Output$10.00 / 1M$6.00 / 1M$10.00 / 1M
Cache Write (5m)$2.00 / 1M$1.20 / 1M$2.00 / 1M
Cache Write (1h)$2.00 / 1M$1.20 / 1M$2.00 / 1M
Cache Read$2.00 / 1M$1.20 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M256K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMoonShot AIAlibabaGoogle
Categorychatchatchat
Charge typePay 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.Qwen3-Max is an updated Qwen3 model with significant gains in reasoning, instruction following, multilingual support, and long-tail knowledge. It improves accuracy in math, coding, logic, and science, reduces hallucinations, and delivers higher-quality open-ended and conversational responses in over 100 languages. Optimized for RAG and tool use, it focuses on reliable final answers rather than a dedicated “thinking” mode.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.