Kimi K3 is a 2.8T-parameter open-weight multimodal model with 1M-token context, native vision, and agentic coding — built for frontier knowledge work.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-kimi-k3-p",
"messages": [{ "role": "user", "content": "Build without permission." }]
}'Overview
Kimi K3 is a 2.8 trillion-parameter Mixture-of-Experts model from Moonshot AI, released in July 2026. It features native vision, a 1-million-token context window, and advanced reasoning for long-horizon coding and agentic knowledge work. As the first open 3T-class model, it supports multimodal input and is optimized for complex, autonomous tasks.
On Venice, Kimi K3 runs with full privacy: zero retention, end-to-end encryption, and execution in a Trusted Execution Environment (TEE). Your prompts are never stored or profiled, even during multimodal or agentic workflows. This means you get uncensored, permissionless access to a frontier model — ideal for sensitive coding, research, or enterprise automation where sovereignty matters.
Agent quickstart
The API is OpenAI-compatible: change the base URL and the model id and existing client code works unchanged.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-kimi-k3-p",
"stream": true,
"messages": [{ "role": "user", "content": "Draft the release note." }]
}'curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-kimi-k3-p",
"messages": [{ "role": "user", "content": "Find the rate limits." }],
"tools": [{
"type": "function",
"function": {
"name": "search_docs",
"description": "Search the API documentation.",
"parameters": {
"type": "object",
"properties": { "query": { "type": "string" } },
"required": ["query"]
}
}
}],
"tool_choice": "auto"
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["VENICE_API_KEY"],
base_url="https://api.venice.ai/api/v1",
)
resp = client.chat.completions.create(
model="e2ee-kimi-k3-p",
messages=[{"role": "user", "content": "Build without permission."}],
)
print(resp.choices[0].message.content)Specifications
Assessment
Use cases
Prompting
Use max reasoning effort for complex coding or research tasks — it improves accuracy at higher cost.
Include screenshots or diagrams as image inputs to ground responses in visual context.
Break long tasks into steps with explicit state tracking — Kimi K3 excels in agentic loops.
Reference external URLs in prompts to trigger web search for up-to-date information.
Use JSON schema in function calls to enforce structured output for downstream parsing.
For cost control, start with low reasoning effort on simple queries before scaling up.
Alternatives
| Model | Best for | Context | Open weights | Price (Venice) |
|---|---|---|---|---|
| Kimi K3 | Long-horizon coding & agents | 1M tokens | Yes | $3.75 in · $18.75 out / 1M |
| Claude Fable 5.1 | General intelligence & safety | 1M tokens | No | $12 in · $60 out / 1M |
| Claude Sonnet 4.6 | Balanced performance | 1M tokens | No | $3.60 in · $18 out / 1M |
| DeepSeek V4 Flash 0731 | Low-cost inference | 1M tokens | Yes | $0.17 in · $0.35 out / 1M |
Kimi K3 is the right pick for teams needing open, private, and agentic AI for long-horizon coding and multimodal knowledge work — especially when sovereignty and fine-tuning matter. For pure cost efficiency, DeepSeek wins; for general reliability, Claude leads.
Pricing
Billed per token on Venice: $3.75 per 1M input tokens and $18.75 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Getting a key
Create a key in API settings. Nothing else is required to start.
Export it as VENICE_API_KEY so the snippets above run unedited.
Point an existing OpenAI client at https://api.venice.ai/api/v1. The scheme is part of the value: an OpenAI client given a bare host does not resolve it.
Pass e2ee-kimi-k3-p as the model and send the request.
FAQ
Kimi K3 is a 2.8 trillion-parameter open-weight AI model from Moonshot AI, released in July 2026. It features a 1-million-token context window, native vision, and advanced reasoning for coding, research, and agentic workflows. It's the first open model in the 3T-parameter class.
On Venice, Kimi K3 costs $3.75 per million input tokens and $18.75 per million output tokens. Cached inputs are billed at $0.38 per million. Pricing is usage-based with no subscription required.
Kimi K3 is open weights but not open source in the traditional sense. The full model is available under the Moonshot K3 License, which allows free use, modification, and commercial deployment — unless your organization exceeds $20M in annual revenue, in which case a separate agreement is required.
Yes, Kimi K3 supports multiple image inputs including JPEG, PNG, WebP, and PDFs up to 20MB each. It uses native vision to understand and reason over visual content alongside text.
Yes, Kimi K3 supports function calling, web search, and code execution — making it ideal for autonomous agents. It can call tools, retrieve live data, and iterate on outputs in a loop.
Kimi K3 leads in long-horizon coding and open-weight flexibility, while Claude Fable 5.1 is more factually reliable and better for general-purpose tasks. Choose Kimi K3 for private, agentic coding; choose Claude for safer, more consistent reasoning.
Kimi K3 has a 1-million-token context window, one of the largest available. This allows it to process entire codebases, long documents, or hours of conversation in a single session.
Yes, Kimi K3 supports tunable reasoning effort — low, high, and max — via API. This lets you balance cost and performance based on task complexity.
One key, free to start, no credit card.