Kling O1 Text-to-Video API: Endpoint & Pricing
Kling O1 Text-to-Video exposes video generation video generation through LLM.API so motion experiments share the same billing and auth as other models.
What is Kling O1 Text-to-Video?
Kling O1 Text-to-Video targets motion content rather than chat. Video generation model by Muapi. On LLM.API it sits alongside other media models under a single developer account.
Can you self-host Kling O1 Text-to-Video?
No. We found no public weights for Kling O1 Text-to-Video on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.
Skip the deploy — use LLM.API as your endpoint
No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, with custom volume discounts on request.
Providers
LLM.API routes Kling O1 Text-to-Video to the providers below, with discounted effective rates versus list price.
List price by provider
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| in —; out $0.0001 per second of video | — | — |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.
Try this model
Test Kling O1 Text-to-Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call Kling O1 Text-to-Video through the OpenAI-compatible API — Video generation via LLM.API (see docs for media endpoints).
Switching from OpenAI? Change 2 lines.
- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"Everything else stays the same — SDK, message format, tools, streaming. Set model to kling-o1-t2v and the call runs unchanged.
curl https://api.llmapi.ai/v1/chat/completions \
-H "Authorization: Bearer $LLMAPI_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "kling-o1-t2v",
"messages": [
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}'from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAPI_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="kling-o1-t2v",
messages=[
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."},
],
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.LLMAPI_KEY,
baseURL: "https://api.llmapi.ai/v1",
});
const resp = await client.chat.completions.create({
model: "kling-o1-t2v",
messages: [
{ role: "user", content: "Give me three crisp launch checklist items." },
],
});
console.log(resp.choices[0].message.content);stream = client.chat.completions.create(
model="kling-o1-t2v",
messages=[{"role": "user", "content": "Write a haiku about latency."}],
stream=True,
)
for chunk in stream:
delta = chunk.choices[0].delta.content
if delta:
print(delta, end="", flush=True){
"model": "kling-o1-t2v",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}ENDPOINTS
Supported endpoints & features
Base URL https://api.llmapi.ai/v1 · model ID kling-o1-t2v · OpenAI-compatible.
POST /v1/chat/completionsChat Completions — supported
| Feature | Status | How to set it |
|---|---|---|
| Function calling (tools) | Not supported | tools, tool_choice |
| Parallel tool calls | Not supported | parallel_tool_calls |
| JSON mode | Not supported | response_format: {"type": "json_object"} |
| Structured outputs | Not supported | response_format: {"type": "json_schema", …} |
| Streaming | Not supported | stream: true |
| Vision (image input) | Not supported | image_url content parts |
| Web search | Not supported | web_search |
ERRORS
Errors & fallback routing
| Code | What it means | What to do |
|---|---|---|
401 | Missing or invalid API key. | Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active. |
429 | Rate limited, or the upstream provider is throttling the request. | Back off and retry with jitter; the gateway also retries the request on another provider where one is available. |
5xx | Upstream provider error or timeout. | Retry; fallback routing sends the retry to the next healthy provider for this model. |
When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.
Kling O1 Text-to-Video in production
What the model is good at.
Short-form content
Fits vertical and horizontal short-form marketing formats. Tuned to how teams typically call Kling O1 Text-to-Video.
Motion coherence
Targets temporally consistent motion across frames for the requested scene.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Relevant for `kling-o1-t2v` workloads on LLM.API.
Product visualization
Helps visualize products and environments before shoot or 3D work. Grounded in the model's video role rather than generic chat claims.
Text-to-video generation
Synthesizes short video clips from prompts for ads, explainers, and social. Grounded in the model's video role rather than generic chat claims.
What you get when you call Kling O1 Text-to-Video through LLM.API.
Unified AI Routing
Reach Kling O1 Text-to-Video and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.Cost Control
Production: Compare provider price points and keep spend visible as you scale Kling O1 Text-to-Video.
More performance, less spend.Reliability Layer
Production: Retry and route across configured providers when a single upstream blips.
Never go dark on users.Observability
Practical: Trace prompts, tokens, and errors for Kling O1 Text-to-Video alongside the rest of your stack.
See every token, everywhere.Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.Model Breadth
Swap Kling O1 Text-to-Video for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.
When to Use — When NOT to Use
Use it if...
- You are building short-form generative video features (Kling O1 Text-to-Video)
- You can tolerate longer generation times than chat (Kling O1 Text-to-Video)
- You need resolution-tiered pricing for motion content (Kling O1 Text-to-Video)
Avoid if...
- You require sub-second interactive generation
- You need broadcast-length films or guaranteed cinema-grade continuity
- You only need still images or chat text
COMMUNITY
What creators say about AI video models
Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Kling O1 Text-to-Video.
- Creator reviews of the latest Kling releases praise multi-shot consistency, native audio and genuine 4K output.
- Comparisons with Sora and Runway focus on prompt adherence and motion stability rather than raw resolution.
- The common workflow advice: generate many short takes cheaply, then upscale or extend the ones that land.
SOURCES
COMMUNITY
What developers say about Kling O1 Text-to-Video
Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.
- Developers note that Kling O1's Multimodal Visual Language (MVL) architecture improves subject consistency across frames because the underlying motion model and identity encoding are shared across its various generation modes.
- Developers on ComfyUI highlight the KlingOmniProTextToVideoNode, which allows for programmatic integration of the model into custom JSON graphs and automated workflows using TypeScript or Python SDKs.
- Technical documentation emphasizes that the Text-to-Video mode utilizes an asynchronous API, requiring developers to fetch results via a task ID after submitting prompts with specific duration and aspect ratio parameters.
SOURCES
Frequently Asked Questions
What modalities does Kling O1 Text-to-Video support?
Kling O1 Text-to-Video accepts text and produces video according to its architecture metadata on LLM.API.
Does Kling O1 Text-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
Can I use tools or structured outputs with Kling O1 Text-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
When should I choose Kling O1 Text-to-Video?
You need resolution-tiered pricing for motion content — especially when you specifically need Kling O1 Text-to-Video.
How do I call Kling O1 Text-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "kling-o1-t2v" and your LLM.API key. See the code snippet on this page.
What is the context length for Kling O1 Text-to-Video?
Reported context for Kling O1 Text-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
Where is the canonical page for Kling O1 Text-to-Video?
https://llmapi.ai/models/openai-kling-o1-t2v/
How is Kling O1 Text-to-Video priced on LLM.API?
Listed pricing metadata shows: $0.06/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
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