Model Cost Pages
High-intent pricing pages for users already comparing OpenAI, Claude, DeepSeek, and more.
Live pricing models
Anthropic Claude models focused on long-context reasoning and stable enterprise usage.
Input: 0.0008 | Output: 0.004
Anthropic Claude models focused on long-context reasoning and stable enterprise usage.
Input: 0.005 | Output: 0.025
Anthropic Claude models focused on long-context reasoning and stable enterprise usage.
Input: 0.005 | Output: 0.025
Anthropic Claude models focused on long-context reasoning and stable enterprise usage.
Input: 0.003 | Output: 0.015
Anthropic Claude models focused on long-context reasoning and stable enterprise usage.
Input: 0.003 | Output: 0.015
DeepSeek models known for cost-efficient reasoning and coding-focused performance.
Input: 0.00014 | Output: 0.00028
DeepSeek models known for cost-efficient reasoning and coding-focused performance.
Input: 0.002 | Output: 0.004
General-purpose model suitable for text generation and reasoning in common API workflows.
Input: 0.00004 | Output: 0.00008
General-purpose model suitable for text generation and reasoning in common API workflows.
Input: 0.0001 | Output: 0.0003
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.0003 | Output: 0.0025
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.0001 | Output: 0.0004
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.0003 | Output: 0.0025
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.00025 | Output: 0.0015
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.002 | Output: 0.01
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.002 | Output: 0.012
Google Gemini models for text, multimodal workloads, and high-throughput inference.
Input: 0.0005 | Output: 0.003
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.002 | Output: 0.008
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.0004 | Output: 0.0016
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.0001 | Output: 0.0004
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.0025 | Output: 0.01
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00015 | Output: 0.0006
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00175 | Output: 0.014
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00175 | Output: 0.014
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00175 | Output: 0.014
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00175 | Output: 0.014
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.0025 | Output: 0.015
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.03 | Output: 0.18
OpenAI general-purpose text and multimodal models for chat, tools, and content generation.
Input: 0.00005 | Output: 0.0004
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.00014 | Output: 0.00222
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.00014 | Output: 0.00222
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.0001 | Output: 0.00292
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.00014 | Output: 0.00222
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.00014 | Output: 0.00806
Moonshot Kimi models designed for long-context processing and Chinese-language Q&A.
Input: 0.00014 | Output: 0.00806
Alibaba Cloud Qwen models optimized for general chat and Chinese language scenarios.
Input: 0.00004 | Output: 0.00008
Alibaba Cloud Qwen models optimized for general chat and Chinese language scenarios.
Input: 0.00012 | Output: 0.00024
Alibaba Cloud Qwen models optimized for general chat and Chinese language scenarios.
Input: 0.0006 | Output: 0.0018
Guides and comparisons
Estimer Claude en séparant input/output et en tenant compte du volume de calls.
Comment estimer les coûts DeepSeek et comparer la valeur quand vous optimisez prompts et retries.
Un cadre simple pour choisir entre GPT-4 et Claude en fonction du total tokens facturés.
Comprendre la tarification Kimi avec input/output tokens + volume d’appels de votre workflow pour mieux contrôler vos dépenses.
Comprendre le coût OpenAI et estimer le coût par token pour input et output.
Estimez le coût Qwen à partir des tokens input/output et du volume d’appels réel — puis optimisez l’endroit où le gaspillage se cache.