tokevenMoonshot (Kimi) · Mid-tier · 256K context window
Kimi K2 pricing for pr review
$0.0196 per call at 8,000 input / 3,000 output tokens.
Per call
$0.0196
10K calls/mo
$196
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 pr review spend. Prices verified daily against provider pricing pages.
Configure your usage
Estimated cost
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=3000,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0196 per call at standard rates
# Input: $0.95/MTok
# Output: $4.00/MTokHow Kimi K2 compares on cost
Per-call cost for all models scoring 50+ on pr review benchmarks. Hover for details.
Highest-quality affordable option: Claude Sonnet 5 at $0.0460/call (2.3x the cost, 96/100 quality). Kimi K2 is already the cheapest choice for pr review.
What drives pr review cost
A pull request review carries the diff, the surrounding context, and often the PR description (heavy input, moderate output). Cost scales with PR size rather than with how much the model says, so the expensive reviews are the ones nobody wants to read anyway. Splitting large PRs is a cost control as much as an engineering practice.
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 8,000/3,000 token split, output accounts for 61% of the $0.0196 per-call cost.
Complete Kimi K2 pricing breakdown
Standard token rates
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $0.95 | 8,000 |
| Output | $4.00 | 3,000 |
Prompt caching: 83% off input tokens
Caching drops input cost from $0.95 to $0.16/MTok. For repeated system prompts, that saves $0.006323 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 volume | Cost per call | Standard monthly | Cached monthly | You save with caching |
|---|---|---|---|---|
| 10,000 calls | $0.0196 | $196 | $132.77 | $63.23 |
| 50,000 calls | $0.0196 | $980 | $663.84 | $316.16 |
| 100,000 calls | $0.0196 | $1,960 | $1,327.68 | $632.32 |
| 500,000 calls | $0.0196 | $9,800 | $6,638.4 | $3,161.6 |
| 1,000,000 calls | $0.0196 | $19,600 | $13,276.8 | $6,323.2 |
Kimi K2 quality benchmarks for pr review
Benchmark data for pr review 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 pr review
6 models score 80+ on pr review benchmarks, sorted by input rate. Cheapest: Claude Sonnet 5 (135% more, 96/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs Kimi |
|---|---|---|---|---|---|---|
| Claude Sonnet 5 | Claude | $2.00 | $10.00 | 96/100 | $0.0460 | 135% more |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 95/100 | $0.0690 | 252% more |
| GPT 5.6 Sol | GPT | $4.00 | $20.00 | 92/100 | $0.0920 | 369% more |
| Claude Opus 4.8 | Claude | $5.00 | $25.00 | 94/100 | $0.1150 | 487% more |
| GPT 5.5 | GPT | $5.00 | $30.00 | 90/100 | $0.1300 | 563% more |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 95/100 | $0.2300 | 1073% 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)
| 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.
Kimi K2 pricing for other use cases
See how Kimi K2 costs change across different workload types.
Code Generation
$0.0179/call
Unit Test Generation
$0.0229/call
SQL Generation
$0.005425/call
API Generation
$0.0268/call
Code Refactoring
$0.0198/call
Code Review
$0.0128/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
Related pages
Frequently asked questions
How much does Kimi K2 cost for pr review per API call?
A typical pr review call using Kimi K2 costs about $0.0196 per call. This estimate uses 8,000 input tokens and 3,000 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 pr review?
Our benchmark data does not yet include a pr review ranking for Kimi K2. We recommend testing it against your own evaluation criteria before production usage.
What is the cheapest model for pr review with good quality?
The most affordable model for pr review above 80/100 quality is Claude Sonnet 5. It comes from Claude at $2.00 per million input tokens. Output costs $10.00 per million tokens with a quality score of 96/100. Claude Sonnet 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 pr review?
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 $0.0196 to about $0.001976 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 pr review 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 pr review, typical calls use 8,000 input and 3,000 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.