Search models/
Models / MoonshotAI / Kimi K2.7 Code

Kimi K2.7 Code APITESTEDOPEN WEIGHTS262K context

by MoonshotAI · text+image->text · released 2026-06-12

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts.

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.74
Output / 1M
$3.50
Context
262K
Our coding score
9/9

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go). Coding score is our own measured result.

✅ First-party tested — we ran Kimi K2.7 Code on our 9-task coding suite

Score
9/9
Cost / 1k tasks
$2.23
Avg latency
11.2s
Reasoning tokens
3,606

Executed against hidden tests at real billed cost — full results · how we test.

What is Kimi K2.7 Code?

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

Kimi K2.7 Code on the release timeline

$2.02$2.66$3.50Kimi K2.7 Code · $3.502025-072026-012026-06
Each point is a kimi k release, placed at its launch date with its current output price (log scale, $/1M). Bubble size ∝ context window; Kimi K2.7 Code is highlighted. Source: provider catalog, verified July 2026.

Kimi K2.7 Code pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

ModelInput / 1MOutput / 1MCache readCache writeContext
Kimi K2.7 Code$0.74$3.50$0.15262K

On output price, Kimi K2.7 Code is cheaper than 32% of the 309 models in the catalog.

What Kimi K2.7 Code costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$71.60
RAG / knowledge base200M / 20M$218
Coding agent80M / 25M$147
Batch extraction150M / 8M$139
Content generation20M / 40M$155

Estimate your own monthly cost

= input × $0.74 + output × $3.50 per 1M · pay-as-you-go, computed in your browser.

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Kimi K2.7 Code vs alternatives

Pick Kimi K2.7 Code when you want its tested 9/9 coding score. If price is the only priority, Kimi K2 0905 is cheaper per token.
ModelInput / 1MOutput / 1MContextOur test
Kimi K2.7 Code$0.74$3.50262K9/9
Kimi K2.6$0.55$3.20262K
Kimi K2 0905$0.60$2.50262K
Kimi K2 Thinking$0.60$2.50262K
Switchpoint Router$0.85$3.40131K
Qwen3 Coder Plus$0.65$3.251M

Specs

Model IDmoonshotai/kimi-k2.7-code
Modalitytext+image->text (input: text, image)
Context window262,144 tokens
Max output16,384 tokens
Tool / function calling✅ Yes
Structured output (JSON)✅ Yes
Released2026-06-12
Open weightsmoonshotai/Kimi-K2.7-Code

How to call Kimi K2.7 Code

from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="moonshotai/kimi-k2.7-code",
    messages=[{"role": "user", "content": "Hello"}],
    # supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)
curl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"moonshotai/kimi-k2.7-code","messages":[{"role":"user","content":"Hello"}]}'
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "moonshotai/kimi-k2.7-code",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Kimi K2.7 Code and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Kimi K2.7 Code

Tips are derived from Kimi K2.7 Code's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Kimi K2.7 Code

Popular open-source projects for running and building with Kimi K2.7 Code — star counts pulled from GitHub (July 2026).

ollama/ollama★ 175.3K
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Go
langgenius/dify★ 147.5K
Production-ready platform for agentic workflow development.
TypeScript
open-webui/open-webui★ 144.0K
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Python
langchain-ai/langchain★ 140.8K
The agent engineering platform.
Python
ggml-org/llama.cpp★ 119.1K
LLM inference in C/C++
C++
vllm-project/vllm★ 85.2K
A high-throughput and memory-efficient inference and serving engine for LLMs
Python

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Kimi K2.7 Code

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → moonshotai/kimi-k2.7-code. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Kimi K2.7 Code ships open weights (moonshotai/Kimi-K2.7-Code), so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across multiple providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.

Related reading

Kimi K2.7-Code Review
DataLLM Lab Blog
Kimi API: Pricing & Keys
DataLLM Lab Blog
Kimi vs DeepSeek
DataLLM Lab Blog

Call Kimi K2.7 Code with one key

300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.

Get an API keyCompare pricing

Frequently asked questions

What is Kimi K2.7 Code?

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It accepts text, image input with a 262K-token context window and was released on 2026-06-12. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Kimi K2.7 Code cost?

On DataLLM Lab it is $0.74 per 1M input tokens and $3.50 per 1M output tokens, with cached input at $0.15/1M — cheaper than about 32% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Kimi K2.7 Code?

262K tokens, with up to 16K max output tokens.

Is Kimi K2.7 Code open source?

Yes — open weights are published on Hugging Face (moonshotai/Kimi-K2.7-Code). You can self-host it or call it via DataLLM Lab.

How do I call the Kimi K2.7 Code API?

Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "moonshotai/kimi-k2.7-code". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.

How did Kimi K2.7 Code score in real testing?

In our executed 9-task coding benchmark it scored 9/9, averaging 11.2s per task at ~$2.23 per 1,000 tasks (real billed cost), generating 3,606 reasoning tokens. See our methodology for scope and limits.