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Models / MoonshotAI / Kimi K2 0711

Kimi K2 0711 APIOPEN WEIGHTS131K context

by MoonshotAI · text->text · released 2025-07-11

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass.

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.57
Output / 1M
$2.30
Context
131K
Providers
1
HF downloads · 30d
420.3K
Cheaper than
40% of catalog

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Kimi K2 0711?

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...

Kimi K2 0711 on the release timeline

$2.02$2.66$3.50Kimi K2 0711 · $2.302025-072026-012026-06
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 0711 is highlighted. Source: provider catalog, verified July 2026.

Kimi K2 0711 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 0711$0.57$2.30131K

On output price, Kimi K2 0711 is cheaper than 40% of the 309 models in the catalog.

What Kimi K2 0711 costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$50.40
RAG / knowledge base200M / 20M$160
Coding agent80M / 25M$103
Batch extraction150M / 8M$104
Content generation20M / 40M$103

Estimate your own monthly cost

= input × $0.57 + output × $2.30 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 0711 vs alternatives

Pick Kimi K2 0711 when you want open weights you can also self-host. If price is the only priority, Kimi K2.5 is cheaper per token.
ModelInput / 1MOutput / 1MContextOur test
Kimi K2 0711$0.57$2.30131K
Kimi K2 0905$0.60$2.50262K
Kimi K2 Thinking$0.60$2.50262K
Kimi K2.5$0.38$2.02262K
MiniMax M1$0.40$2.201M
GLM 4.5$0.60$2.20131K

When not to use Kimi K2 0711

Specs

Model IDmoonshotai/kimi-k2
Modalitytext->text (input: text)
Context window131,072 tokens
Max output100,352 tokens
Tool / function calling✅ Yes
Structured output (JSON)
Released2025-07-11
Knowledge cutoff2024-12-31
Open weightsmoonshotai/Kimi-K2-Instruct · 420.3K downloads / 2.4K likes (30d)

How to call Kimi K2 0711

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",
    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","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",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Kimi K2 0711 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Kimi K2 0711

Tips are derived from Kimi K2 0711's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Kimi K2 0711

Popular open-source projects for running and building with Kimi K2 0711 — 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 0711

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. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Kimi K2 0711 ships open weights (moonshotai/Kimi-K2-Instruct, ~420.3K downloads and 2.4K likes in the last 30 days), with community quantizations (fp8) for smaller GPUs, 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 1 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 API: Pricing & Keys
DataLLM Lab Blog
Kimi vs DeepSeek
DataLLM Lab Blog
How OpenAI-Compatible APIs Work
DataLLM Lab Blog

Call Kimi K2 0711 with one key

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

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Frequently asked questions

What is Kimi K2 0711?

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It accepts text input with a 131K-token context window and was released on 2025-07-11. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Kimi K2 0711 cost?

On DataLLM Lab it is $0.57 per 1M input tokens and $2.30 per 1M output tokens — cheaper than about 40% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Kimi K2 0711?

131K tokens, with up to 100K max output tokens.

Is Kimi K2 0711 open source?

Yes — open weights are published on Hugging Face (moonshotai/Kimi-K2-Instruct), with about 420.3K downloads and 2.4K likes in the last 30 days. You can self-host it or call it via DataLLM Lab.

How do I call the Kimi K2 0711 API?

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

What are good alternatives to Kimi K2 0711?

Close options by price and capability include Kimi K2 0905, Kimi K2 Thinking, Kimi K2.5 — all callable with the same DataLLM Lab key.