---
title: "Kimi-K2.6 Cost Calculator - Wandb"
description: "Calculate the cost of using Kimi-K2.6 from Wandb. Input costs $0.65 and output $3.41 per 1M tokens."
url: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/kimi-k2.6"
markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/kimi-k2.6.md"
---

# Kimi-K2.6 Cost Calculator - Wandb

> Calculate the cost of using Kimi-K2.6 from Wandb. Input costs $0.65 and output $3.41 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-K2.6

Kimi-K2.6 is a chat model from Wandb, one of 35 chat models they offer. It is priced at $0.65 per 1M input tokens and $3.41 per 1M output tokens, ranking 1803 out of 3254 chat models by cost and cheaper than 45% of models in this category. Kimi-K2.6 supports vision, prompt caching — one of only 7 chat models with this combination. Its 262K-token context window is in the top 37% among chat models.

## Pricing

Published Wandb pricing for Kimi-K2.6.

- **$0.65 / 1M tokens Input.**
- **$3.41 / 1M tokens Output.**

## Technical Specifications

- **Chat Mode.**
- **262,144 Max Input Tokens.**
- **262,144 Max Tokens.**

## Model Capabilities

Kimi-K2.6 supports: Vision, Prompt Caching.

## How Pricing Compares

At $0.65 per 1M input tokens and $3.41 per 1M output tokens, Kimi-K2.6 ranks 1803 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 45% of models in this category.

Kimi-K2.6 is one of 35 Wandb chat models, one of only 7 chat models combining prompt caching, vision. its 262K-token context window places it in the top 37% of chat models.

| Model | Provider | Input $/1M | Output $/1M | vs Kimi-K2.6 |
| --- | --- | --- | --- | --- |
| amazon.nova-pro-v1:0 | AWS Bedrock | $0.80 | $3.20 | +23% |
| gpt-5.4-mini | Azure | $0.75 | $4.50 | +15% |
| gpt-5.4-mini-2026-03-17 | Azure | $0.75 | $4.50 | +15% |
| FW-Kimi-K2.5 | Azure | $0.66 | $3.30 | +2% |
| databricks-gemini-3-flash | Databricks | $0.63 | $3.75 | -4% |

## More from Wandb

- [Kimi-K2-Instruct ($0.60/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/kimi-k2-instruct.md)
- [Kimi-K2.5 ($0.60/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/kimi-k2.5.md)
- [Qwen3.6-27B ($0.60/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/qwen3.6-27b.md)
- [Llama-3.3-70B-Instruct ($0.71/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/llama-3.3-70b-instruct.md)

## Related Resources

- [All Wandb pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb.md)

## FAQ

### Is Kimi-K2.6 cheaper than amazon.nova-pro-v1:0?

Yes. Kimi-K2.6 costs $0.65 per 1M input tokens compared to amazon.nova-pro-v1:0's $0.80 per 1M input tokens, making it 23% more affordable. Both are chat models and share support for vision, function calling, prompt caching, structured output.

### How does Kimi-K2.6 pricing compare to the average chat model?

Kimi-K2.6 input pricing is $0.65 per 1M tokens, which is 26% above the median of $0.52 for chat models. It ranks 1803 out of 3254 chat models by input cost, making it cheaper than 45% of models in this category. For output, it costs $3.41 per 1M tokens compared to the median of $1.50.

### What makes Kimi-K2.6 different from other Wandb models?

Among Wandb's 35 chat models, Kimi-K2.6 ranks 28 by input cost. Its combination of prompt caching, vision is shared by only 6 other chat models.

### What are the best alternatives to Kimi-K2.6?

The most comparable chat models to Kimi-K2.6 are: amazon.nova-pro-v1:0 from AWS Bedrock ($0.80/1M input tokens); gpt-5.4-mini from Azure ($0.75/1M input tokens); gpt-5.4-mini-2026-03-17 from Azure ($0.75/1M input tokens); FW-Kimi-K2.5 from Azure ($0.66/1M 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-K2.6 costs?

Kimi-K2.6 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 $0.65 and generating 1M output tokens costs $3.41.

## Related Resources

- [All Wandb pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb.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/wandb/model/kimi-k2.6](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/wandb/model/kimi-k2.6) for AI/LLM consumption.*
