--- title: "kimi-k2-instruct Cost Calculator - Novita" description: "Calculate the cost of using kimi-k2-instruct from Novita. Input costs $0.57 and output $2.30 per 1M tokens." url: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/kimi-k2-instruct" markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/kimi-k2-instruct.md" --- # kimi-k2-instruct Cost Calculator - Novita > Calculate the cost of using kimi-k2-instruct from Novita. Input costs $0.57 and output $2.30 per 1M tokens. ## Important Links - [View MCP Gateway](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources/mcp-gateway.md) - [Features](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/#features) - [Enterprise](https://www.getmaxim.ai/enterprise) - [Pricing](https://www.getmaxim.ai/pricing) - [Docs](https://docs.getbifrost.ai) - [GitHub](https://github.com/maximhq/bifrost) - [Book a Demo](https://www.getmaxim.ai/book-a-demo) ## About kimi-k2-instruct kimi-k2-instruct is a chat model from Novita, one of 130 chat models they offer. It is priced at $0.57 per 1M input tokens and $2.30 per 1M output tokens, ranking 1658 out of 3254 chat models by cost and cheaper than 49% of models in this category. kimi-k2-instruct supports function calling, structured output. It accepts up to 131K input tokens. ## Pricing Published Novita pricing for kimi-k2-instruct. - **$0.57 / 1M tokens Input.** - **$2.30 / 1M tokens Output.** ## Technical Specifications - **Chat Mode.** - **131,072 Max Input Tokens.** - **100,352 Max Output Tokens.** - **100,352 Max Tokens.** ## Model Capabilities kimi-k2-instruct supports: Function Calling, Parallel Function Calling, System Messages, Response Schema, Tool Choice. ## How Pricing Compares At $0.57 per 1M input tokens and $2.30 per 1M output tokens, kimi-k2-instruct ranks 1658 out of 3254 chat models by input cost. It is more expensive compared to the median of $0.52 for chat models, and is cheaper than 49% of models in this category. kimi-k2-instruct is one of 130 Novita chat models, with support for function calling, structured output. | Model | Provider | Input $/1M | Output $/1M | vs kimi-k2-instruct | | --- | --- | --- | --- | --- | | deepseek-v3p2 | Fireworks AI | $0.56 | $1.68 | -2% | | glm-4p5 | Fireworks AI | $0.55 | $2.19 | -4% | | glm-4p6 | Fireworks AI | $0.55 | $2.19 | -4% | | glm-4p7 | Fireworks AI | $0.60 | $2.20 | +5% | | kimi-k2-instruct | Fireworks AI | $0.60 | $2.50 | +5% | ## More from Novita - [glm-4.6 ($0.55/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/glm-4.6.md) - [minimax-m1-80k ($0.55/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/minimax-m1-80k.md) - [glm-4-32b-0414 ($0.55/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/glm-4-32b-0414.md) - [glm-4.7 ($0.60/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/glm-4.7.md) ## Related Resources - [All Novita pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita.md) ## FAQ ### Is kimi-k2-instruct cheaper than deepseek-v3p2? No. kimi-k2-instruct costs $0.57 per 1M input tokens while deepseek-v3p2 costs $0.56 per 1M input tokens, making deepseek-v3p2 2% more affordable for input. However, kimi-k2-instruct may offer different capabilities or performance characteristics that justify the price difference. ### How does kimi-k2-instruct pricing compare to the average chat model? kimi-k2-instruct input pricing is $0.57 per 1M tokens, which is 10% above the median of $0.52 for chat models. It ranks 1658 out of 3254 chat models by input cost, making it cheaper than 49% of models in this category. For output, it costs $2.30 per 1M tokens compared to the median of $1.50. ### What makes kimi-k2-instruct different from other Novita models? Among Novita's 130 chat models, kimi-k2-instruct ranks 91 by input cost. ### What are the best alternatives to kimi-k2-instruct? The most comparable chat models to kimi-k2-instruct are: deepseek-v3p2 from Fireworks AI ($0.56/1M input tokens); glm-4p5 from Fireworks AI ($0.55/1M input tokens); glm-4p6 from Fireworks AI ($0.55/1M input tokens); glm-4p7 from Fireworks AI ($0.60/1M input tokens). These alternatives were selected based on similar capabilities, pricing, and provider diversity. You can compare any of these models in detail using the Bifrost Model Library. ### How do I calculate kimi-k2-instruct costs? kimi-k2-instruct is priced based on input and output tokens. Use the interactive calculator at the top of this page to estimate costs for your specific workload. Enter your expected input and output tokens volume and the calculator will show the total cost breakdown. For reference, processing 1M input tokens costs $0.57 and generating 1M output tokens costs $2.30. ## Related Resources - [All Novita pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita.md) - [LLM cost calculator](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator.md) - [Model library](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library.md) - [Docs: Bifrost docs](https://docs.getbifrost.ai) - [GitHub: maximhq/bifrost](https://github.com/maximhq/bifrost) - [Pricing: Bifrost pricing](https://www.getmaxim.ai/pricing) - [Enterprise: Bifrost enterprise](https://www.getmaxim.ai/enterprise) - [Book a Demo: Bifrost demo](https://www.getmaxim.ai/book-a-demo) - [Resources: Bifrost resources](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources.md) --- *This is a markdown version of [https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/kimi-k2-instruct](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/novita/model/kimi-k2-instruct) for AI/LLM consumption.*