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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. GPT-5 ProOpenAIRemove
kimi-k3.1-pro vs gemini-4-argon vs gpt-5-pro
AttributeKimi K3.1 Prokimi-k3.1-proGemini 4 Argongemini-4-argonGPT-5 Progpt-5-pro
Pricing
Input$2.00 / 1M$2.00 / 1M$7.50 / 1M
Output$10.00 / 1M$10.00 / 1M$60.00 / 1M
Cache Write (5m)$2.00 / 1M$2.00 / 1M$7.50 / 1M
Cache Write (1h)$2.00 / 1M$2.00 / 1M$7.50 / 1M
Cache Read$2.00 / 1M$2.00 / 1M$7.50 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M400K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMoonShot AIGoogleOpenAI
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.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.GPT-5 Pro is OpenAI's top model, optimized for complex, high-stakes tasks that require careful step-by-step reasoning and precise instruction following. It delivers stronger code quality, clearer writing, and better factual reliability, with support for test-time routing and intent cues like “think hard about this.” It also reduces hallucinations and sycophancy while improving performance across coding, writing, and health-related workloads.