Kimi K2 0711 APIOPEN WEIGHTS131K context
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.
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
Kimi K2 0711 pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| Kimi K2 0711 | $0.57 | $2.30 | — | — | 131K |
On output price, Kimi K2 0711 is cheaper than 40% of the 309 models in the catalog.
What Kimi K2 0711 costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $50.40 |
| RAG / knowledge base | 200M / 20M | $160 |
| Coding agent | 80M / 25M | $103 |
| Batch extraction | 150M / 8M | $104 |
| Content generation | 20M / 40M | $103 |
Estimate your own monthly cost
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
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| Kimi K2 0711 | $0.57 | $2.30 | 131K | — |
| Kimi K2 0905 | $0.60 | $2.50 | 262K | — |
| Kimi K2 Thinking | $0.60 | $2.50 | 262K | — |
| Kimi K2.5 | $0.38 | $2.02 | 262K | — |
| MiniMax M1 | $0.40 | $2.20 | 1M | — |
| GLM 4.5 | $0.60 | $2.20 | 131K | — |
When not to use Kimi K2 0711
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | moonshotai/kimi-k2 |
| Modality | text->text (input: text) |
| Context window | 131,072 tokens |
| Max output | 100,352 tokens |
| Tool / function calling | ✅ Yes |
| Structured output (JSON) | — |
| Released | 2025-07-11 |
| Knowledge cutoff | 2024-12-31 |
| Open weights | ✅ moonshotai/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
- Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — Kimi K2 0711 follows concrete instructions better than abstract ones.
- Give it real tools. Pass a
tools=[...]schema instead of asking it to "pretend" — let Kimi K2 0711 emit tool calls, execute them, and feed results back for the next turn.
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).
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
Call Kimi K2 0711 with one key
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Get an API keyCompare pricingFrequently 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.