Moonshot (Kimi) · Flagship · 1M context window
$0.0495 per call at 1,500 input / 3,000 output tokens.
Per call
$0.0495
10K calls/mo
$495
Cache savings
90% off input
Batch savings
0% off all
Adjust token counts, volume, and discount toggles to model your math reasoning spend. Prices verified daily against provider pricing pages.
Call Kimi K3 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-k3",
max_tokens=3000,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0495 per call at standard rates
# Input: $3.00/MTok
# Output: $15.00/MTokPer-call cost for all models scoring 50+ on math reasoning benchmarks. Hover for details.
Cheapest viable option: GPT 5.6 Luna at $0.003900/call (92% less, 86/100 quality).
Short problems, long solutions. Input is trivial and output is large because the derivation is the answer, so output rate is effectively the only price that matters. Models differ sharply in how much they show their working, which means two models at the same output rate can differ substantially in real cost per problem.
For Kimi K3 specifically, that means output tokens cost 5.0x more than input, at $15.00 vs $3.00 per MTok. At this use case’s 1,500/3,000 token split, output accounts for 91% of the $0.0495 per-call cost.
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $3.00 | 1,500 |
| Output | $15.00 | 3,000 |
Caching drops input cost from $3.00 to $0.30/MTok. For repeated system prompts, that saves $0.004050 per call.
Submit requests asynchronously and receive 0% 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 | $0.0495 | $495 | $454.5 | $40.5 |
| 50,000 calls | $0.0495 | $2,475 | $2,272.5 | $202.5 |
| 100,000 calls | $0.0495 | $4,950 | $4,545 | $405 |
| 500,000 calls | $0.0495 | $24,750 | $22,725 | $2,025 |
| 1,000,000 calls | $0.0495 | $49,500 | $45,450 | $4,050 |
Benchmark data for math reasoning is pending for Kimi K3. Test against your own evaluation suite before moving to production.
Benchmark data is not yet available for Kimi K3. We recommend testing against your own evaluation criteria.
22 models score 80+ on math reasoning benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (92% less, 86/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs Kimi |
|---|---|---|---|---|---|---|
| GPT 5.6 Luna | GPT | $0.20 | $1.20 | 86/100 | $0.003900 | 92% cheaper |
| Gemini 3.6 Flash | Gemini | $0.75 | $3.75 | 85/100 | $0.0124 | 75% cheaper |
| Gemini 3.7 Flash | Gemini | $0.75 | $3.75 | 88/100 | $0.0124 | 75% cheaper |
| Gemini 3.8 Flash | Gemini | $0.75 | $3.75 | 89/100 | $0.0124 | 75% cheaper |
| Claude Sonnet 5 | Claude | $2.00 | $10.00 | 89/100 | $0.0330 | 33% cheaper |
| GPT 5.6 Terra | GPT | $2.00 | $12.00 | 91/100 | $0.0390 | 21% cheaper |
| GPT 6 Sol | GPT | $2.00 | $10.00 | 89/100 | $0.0330 | 33% cheaper |
| Gemini 3.1 Pro | Gemini | $2.00 | $12.00 | 84/100 | $0.0390 | 21% cheaper |
| Grok 4.6 | Grok | $2.00 | $6.00 | 91/100 | $0.0210 | 58% cheaper |
| Grok 4.5 | Grok | $2.00 | $6.00 | 87/100 | $0.0210 | 58% cheaper |
| GPT 5.4 | GPT | $2.50 | $15.00 | 88/100 | $0.0488 | 2% cheaper |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 85/100 | $0.0495 | same cost |
| Claude Opus 5.5 | Claude | $4.00 | $20.00 | 92/100 | $0.0660 | 33% more |
| GPT 5.6 Sol | GPT | $4.00 | $20.00 | 92/100 | $0.0660 | 33% more |
| Claude Opus 4.8 | Claude | $5.00 | $25.00 | 89/100 | $0.0825 | 67% more |
| Claude Opus 5 | Claude | $5.00 | $25.00 | 91/100 | $0.0825 | 67% more |
| Claude Opus 4.7 | Claude | $5.00 | $25.00 | 87/100 | $0.0825 | 67% more |
| Claude Opus 4.6 | Claude | $5.00 | $25.00 | 89/100 | $0.0825 | 67% more |
| GPT 5.5 | GPT | $5.00 | $30.00 | 90/100 | $0.0975 | 97% more |
| Claude Fable 5.1 | Claude | $10.00 | $50.00 | 92/100 | $0.1650 | 233% more |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 90/100 | $0.1650 | 233% more |
| GPT 6 Astra | GPT | $10.00 | $50.00 | 93/100 | $0.1650 | 233% more |
Provider
Moonshot (Kimi)
Tier
Flagship
Context
1M tokens
Released
Not published
Prices from platform.kimi.ai (read 2026-10-11). Cache hit: $0.30/MTok input. Kimi K3 is a 2.8T-parameter open-weight MoE model. No batch discount published yet. Not yet benchmarked, so never recommended.
| Model | Tier | Input $/MTok | Output $/MTok | Context |
|---|---|---|---|---|
| Kimi K2 | Mid-tier | $0.95 | $4.00 | 256K |
You can compare Kimi K3 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 K3 costs change across different workload types.
Code Generation
$0.0660/call
Unit Test Generation
$0.0840/call
SQL Generation
$0.0195/call
API Generation
$0.0990/call
Code Refactoring
$0.0720/call
Code Review
$0.0450/call
PR Review
$0.0690/call
Security Review
$0.0555/call
Bug Detection
$0.0450/call
Document Summarization
$0.0450/call
PDF Summarization
$0.0675/call
Meeting Notes
$0.0540/call
Email Summarization
$0.0165/call
Chatbot
$0.0210/call
RAG Pipeline
$0.0405/call
Customer Support Bot
$0.0240/call
FAQ Bot
$0.0165/call
Data Extraction
$0.0270/call
JSON Extraction
$0.0210/call
Invoice Parsing
$0.0150/call
Resume Parsing
$0.0195/call
Chain of Thought
$0.0840/call
Legal Analysis
$0.0900/call
Financial Analysis
$0.0840/call
Content Moderation
$0.003000/call
Sentiment Analysis
$0.003000/call
Categorization
$0.004650/call
Intent Detection
$0.002400/call
Copywriting
$0.0315/call
Blog Writing
$0.1230/call
Marketing Copy
$0.0474/call
Product Descriptions
$0.0240/call
A typical math reasoning call using Kimi K3 costs about $0.0495 per call. This estimate uses 1,500 input tokens and 3,000 output tokens at standard rates. Standard rates are $3.00 per million input tokens and $15.00 per million output tokens.
Our benchmark data does not yet include a math reasoning ranking for Kimi K3. We recommend testing it against your own evaluation criteria before production usage.
The most affordable model for math reasoning above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 86/100. Switching from Kimi K3 to GPT 5.6 Luna saves about 92% per API call.
Three strategies lower Kimi K3 costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 0% 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 $0.0495 to about $0.004950 per call.
Moonshot (Kimi) has 1 other models alongside Kimi K3 today: Kimi K2 at $0.95/$4.00 per million tokens (mid-tier). The right choice depends on whether your math reasoning workload prioritizes quality, cost, or speed.
Kimi K3 supports a context window of 1M tokens per API call. This sets the maximum combined length of your input prompt and generated response. For math reasoning, typical calls use 1,500 input and 3,000 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.