Moonshot (Kimi) · Mid-tier · 256K context window
$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
Adjust token counts, volume, and discount toggles to model your sql generation spend. Prices verified daily against provider pricing pages.
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/MTokPer-call cost for all models scoring 50+ on sql generation benchmarks. Hover for details.
Highest-quality affordable option: Claude Haiku 4.5 at $0.006500/call (1.2x the cost, 72/100 quality). Kimi K2 is already the cheapest choice for sql generation.
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.
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $0.95 | 1,500 |
| Output | $4.00 | 1,000 |
Caching drops input cost from $0.95 to $0.16/MTok. For repeated system prompts, that saves $0.001186 per call.
Submit requests asynchronously and receive 40% off all token costs. This works best for offline pipelines where latency requirements are flexible.
| Monthly volume | Cost per call | Standard monthly | Cached monthly | You 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 |
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.
5 models score 80+ on sql generation benchmarks, sorted by input rate. Cheapest: Claude Haiku 4.5 (20% more, 72/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs Kimi |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | Claude | $1.00 | $5.00 | 72/100 | $0.006500 | 20% more |
| Claude Opus 5.5 | Claude | $4.00 | $20.00 | 79/100 | $0.0260 | 379% more |
| Claude Opus 5 | Claude | $5.00 | $25.00 | 72/100 | $0.0325 | 499% more |
| Claude Fable 5.1 | Claude | $10.00 | $50.00 | 74/100 | $0.0650 | 1098% more |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 72/100 | $0.0650 | 1098% more |
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.
| Model | Tier | Input $/MTok | Output $/MTok | Context |
|---|---|---|---|---|
| Kimi K3 | Flagship | $3.00 | $15.00 | 1M |
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.
See how Kimi K2 costs change across different workload types.
Code Generation
$0.0179/call
Unit Test Generation
$0.0229/call
API Generation
$0.0268/call
Code Refactoring
$0.0198/call
Code Review
$0.0128/call
PR Review
$0.0196/call
Security Review
$0.0157/call
Bug Detection
$0.0128/call
Document Summarization
$0.0135/call
PDF Summarization
$0.0202/call
Meeting Notes
$0.0156/call
Email Summarization
$0.004850/call
Chatbot
$0.005900/call
RAG Pipeline
$0.0117/call
Customer Support Bot
$0.006850/call
FAQ Bot
$0.004625/call
Data Extraction
$0.007800/call
JSON Extraction
$0.006050/call
Invoice Parsing
$0.004300/call
Resume Parsing
$0.005575/call
Chain of Thought
$0.0229/call
Legal Analysis
$0.0255/call
Math Reasoning
$0.0134/call
Financial Analysis
$0.0236/call
Content Moderation
$0.000875/call
Sentiment Analysis
$0.000875/call
Categorization
$0.001360/call
Intent Detection
$0.000685/call
Copywriting
$0.008475/call
Blog Writing
$0.0330/call
Marketing Copy
$0.0128/call
Product Descriptions
$0.006475/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.
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.
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.
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.
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.
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.
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.