Moonshot (Kimi) · Mid-tier · 256K context window

Kimi K2 pricing for sql generation

$0.005425 per call at 1,500 input / 1,000 output tokens.

Per call

$0.005425

10K calls/mo

$54.25

Cache savings

83% off input

Batch savings

40% off all

Calculate your Kimi K2 costs

Adjust token counts, volume, and discount toggles to model your sql generation spend. Prices verified daily against provider pricing pages.

Configure your usage

1,500
100100K
1,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$54
10,000 calls/month
Cost per call$0.005425
Daily cost$2
Input rate$0.95/MTok
Output rate$4.00/MTok
Analyze your real spend

Quick start

Call Kimi K2 with the OpenAI Python SDK pointed at api.moonshot.cn:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.moonshot.cn/v1",
    api_key=os.environ["MOONSHOT_API_KEY"],
)
response = client.chat.completions.create(
    model="kimi-k2",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.005425 per call at standard rates
# Input:  $0.95/MTok
# Output: $4.00/MTok

What drives sql generation cost

The cheapest code use case on this list. A natural-language question plus a schema fits in 1.5K tokens, and the query that comes back is under 1K. That makes SQL generation a genuine candidate for a fast-tier model: the task is well-bounded, the output is short, and the quality gap between tiers narrows when there is little room to go wrong. Schema caching cuts the input side to near zero.

For Kimi K2 specifically, that means output tokens cost 4.2x more than input, at $4.00 vs $0.95 per MTok. At this use case’s 1,500/1,000 token split, output accounts for 74% of the $0.005425 per-call cost.

Complete Kimi K2 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.951,500
Output$4.001,000

Prompt caching: 83% off input tokens

Caching drops input cost from $0.95 to $0.16/MTok. For repeated system prompts, that saves $0.001186 per call.

Batch API: 40% off all tokens

Submit requests asynchronously and receive 40% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.005425$54.25$42.39$11.86
50,000 calls$0.005425$271.25$211.97$59.28
100,000 calls$0.005425$542.5$423.94$118.56
500,000 calls$0.005425$2,712.5$2,119.7$592.8
1,000,000 calls$0.005425$5,425$4,239.4$1,185.6

Kimi K2 quality benchmarks for sql generation

Benchmark data for sql generation is pending for Kimi K2. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for Kimi K2. We recommend testing against your own evaluation criteria.

Alternative models for sql generation

5 models score 80+ on sql generation benchmarks, sorted by input rate. Cheapest: Claude Haiku 4.5 (20% more, 72/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Kimi
Claude Haiku 4.5Claude$1.00$5.0072/100$0.00650020% more
Claude Opus 5.5Claude$4.00$20.0079/100$0.0260379% more
Claude Opus 5Claude$5.00$25.0072/100$0.0325499% more
Claude Fable 5.1Claude$10.00$50.0074/100$0.06501098% more
Claude Fable 5Claude$10.00$50.0072/100$0.06501098% more

About Kimi K2

Provider

Moonshot (Kimi)

Tier

Mid-tier

Context

256K tokens

Released

Not published

Prices from platform.kimi.ai (K2.6, read 2026-10-11). Cache hit: $0.16/MTok input. Batch API at 60% of standard rate. Not yet benchmarked, so never recommended.

Other models from Moonshot (Kimi)

ModelTierInput $/MTokOutput $/MTokContext
Kimi K3Flagship$3.00$15.001M

You can compare Kimi K2 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does Kimi K2 cost for sql generation per API call?

A typical sql generation call using Kimi K2 costs about $0.005425 per call. This estimate uses 1,500 input tokens and 1,000 output tokens at standard rates. Standard rates are $0.95 per million input tokens and $4.00 per million output tokens.

Is Kimi K2 the best model for sql generation?

Our benchmark data does not yet include a sql generation ranking for Kimi K2. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for sql generation with good quality?

The most affordable model for sql generation above 80/100 quality is Claude Haiku 4.5. It comes from Claude at $1.00 per million input tokens. Output costs $5.00 per million tokens with a quality score of 72/100. Claude Haiku 4.5 costs more per call than Kimi K2 but scores higher on quality benchmarks for this task type.

How can I reduce my Kimi K2 costs for sql generation?

Three strategies lower Kimi K2 costs for this task type effectively. Prompt caching gives a 83% discount on input tokens when reusing system prompts. The batch API gives 40% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.005425 to about $0.000547 per call.

How does Kimi K2 pricing compare to other Moonshot (Kimi) models?

Moonshot (Kimi) has 1 other models alongside Kimi K2 today: Kimi K3 at $3.00/$15.00 per million tokens (flagship). The right choice depends on whether your sql generation workload prioritizes quality, cost, or speed.

What context window does Kimi K2 support?

Kimi K2 supports a context window of 256K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For sql generation, typical calls use 1,500 input and 1,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.