How much does the Moonshot API cost?

Moonshot API pricing: Kimi K2.6 costs $0.95/$4.00 per 1M tokens (input/output). Kimi K2.6 offers a 256K context window and is optimized for long-context reasoning, document analysis, and multi-turn conversations.

Is Moonshot cheaper than GPT-5?

Yes, significantly. Kimi K2.6 ($0.95/$4.00 per 1M tokens) is 24% cheaper than GPT-5 ($1.25/$10.00) for input tokens and 60% cheaper for output tokens. It offers strong long-context performance at a competitive price point.

How much does Moonshot cost per month?

Monthly Moonshot costs depend on usage: 100 requests/day (~3K/mo) costs ~$15/month. 1,000 requests/day (~30K/mo) costs ~$150/month. At 10,000 requests/day, costs are ~$1,500/month. Kimi K2.6 is most cost-effective for long-context workloads.

What is Kimi K2.6 used for?

Kimi K2.6 ($0.95/$4.00 per 1M tokens) excels at long-context reasoning with a 256K context window. It's ideal for document analysis, book-length summarization, multi-turn conversations, and tasks requiring extensive context. Popular for research, legal, and enterprise use cases.

Moonshot API Cost Calculator

Estimate your Moonshot spend on Kimi K2.6. See cost per request, per 1K requests, and monthly totals. Optimized for long-context reasoning with a 256K context window.

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Cheaper Alternatives from Other Providers

These models from other providers offer similar capabilities at lower prices:

Model	Provider	Input/1M	Output/1M	Your Cost/Req	Savings vs Selected

Moonshot API Pricing Explained

Moonshot AI offers Kimi K2.6 ($0.95/$4.00 per 1M tokens), a model optimized for long-context reasoning with a 256K context window. Kimi excels at document analysis, multi-turn conversations, and tasks requiring extensive context — making it ideal for research, legal, and enterprise applications.

When to Use Kimi K2.6

Document analysis: Process entire books, legal contracts, or research papers in a single request. The 256K context window handles documents that would require chunking with other models.
Long-context reasoning: Tasks that require understanding relationships across distant parts of a document. Kimi's architecture is specifically optimized for this.
Multi-turn conversations: Maintain extensive conversation history without losing context. Ideal for complex customer support and research assistants.
Summarization: Condense long documents, reports, or transcripts into concise summaries with accurate coverage.

Moonshot vs Competitors

Moonshot's biggest advantage is long-context performance at a competitive price. Kimi K2.6 ($0.95/$4.00) is 24% cheaper than GPT-5 for input tokens while offering a 256K context window. For long-document workloads, Kimi often delivers better cost-per-quality than models with smaller context windows that require chunking.

How to Reduce Your Moonshot API Costs

Leverage the 256K context window: Include all relevant context in a single request instead of making multiple smaller calls. This reduces per-request overhead.
Batch documents: Process multiple documents in a single prompt to maximize the context window efficiency.
Set token limits: Control output length with max_tokens to avoid surprise costs on verbose responses.
Use for right workloads: Kimi is most cost-effective for long-context tasks. For short queries, consider cheaper alternatives like DeepSeek V4 Flash.

Moonshot Free Tier

Moonshot offers free API credits for new accounts. This is enough for prototyping and evaluation. Production usage requires a paid plan with competitive per-token pricing.

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