How is Kling V2.5 Turbo Pro Text-to-Video priced on LLM.API?

Listed pricing metadata shows: $0.07/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

What are limitations of Kling V2.5 Turbo Pro Text-to-Video?

Like other API models, Kling V2.5 Turbo Pro Text-to-Video can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

How long do Kling V2.5 Turbo Pro Text-to-Video jobs take?

Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.

Can I use tools or structured outputs with Kling V2.5 Turbo Pro Text-to-Video?

Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.

Which providers serve Kling V2.5 Turbo Pro Text-to-Video?

LLM.API currently lists: muapi. Availability can vary by region and account.

What is the context length for Kling V2.5 Turbo Pro Text-to-Video?

Reported context for Kling V2.5 Turbo Pro Text-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.

Does Kling V2.5 Turbo Pro Text-to-Video support streaming?

Streaming depends on the active provider; check the providers table on this page for flags.

Which endpoint do I call for Kling V2.5 Turbo Pro Text-to-Video?

POST https://api.llmapi.ai/v1/chat/completions with model "kling-v2.5-turbo-pro-t2v" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to Kling V2.5 Turbo Pro Text-to-Video on LLM.API?

Change two lines: set base_url to https://api.llmapi.ai/v1 and api_key to your LLM.API key. The rest of your OpenAI SDK code stays the same.

Does Kling V2.5 Turbo Pro Text-to-Video support function calling and structured outputs?

Function calling: not supported. Structured outputs: not supported.

Kling V2.5 Turbo Pro Text-to-Video API: Endpoint & Pricing

Kling V2.5 Turbo Pro Text-to-Video exposes video generation video generation through LLM.API so motion experiments share the same billing and auth as other models.

Start Using API

What is Kling V2.5 Turbo Pro Text-to-Video?

Kling V2.5 Turbo Pro 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 V2.5 Turbo Pro Text-to-Video?

No. We found no public weights for Kling V2.5 Turbo Pro 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, up to 30% below list price.

Get API key See API code ↓

Providers

LLM.API routes Kling V2.5 Turbo Pro Text-to-Video to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput

muapi$0 in

$0.0001 out

Provider list prices; the LLM.API discount applies on top.

Provider	Pricing	Context	Capabilities
muapi	in —; out $0.0001 per second of video	—	—

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 8 Oct 2026.

Try this model

Test Kling V2.5 Turbo Pro Text-to-Video right here — free to start.

Kling V2.5 Turbo Pro Text-to-Video

Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Kling V2.5 Turbo Pro 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-v2.5-turbo-pro-t2v and the call runs unchanged.

bash

curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-v2.5-turbo-pro-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-v2.5-turbo-pro-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-v2.5-turbo-pro-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-v2.5-turbo-pro-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-v2.5-turbo-pro-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-v2.5-turbo-pro-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 V2.5 Turbo Pro Text-to-Video in production

Best workloadsLLM.API features

What the model is good at.

Product visualization
Helps visualize products and environments before shoot or 3D work. Relevant for `kling-v2.5-turbo-pro-t2v` workloads on LLM.API.
Text-to-video generation
Synthesizes short video clips from prompts for ads, explainers, and social. Relevant for `kling-v2.5-turbo-pro-t2v` workloads on LLM.API.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Relevant for `kling-v2.5-turbo-pro-t2v` workloads on LLM.API.
Motion coherence
Targets temporally consistent motion across frames for the requested scene. Reflects video generation positioning for this endpoint.
Resolution options
Supports multiple output resolutions depending on provider pricing tiers. Tuned to how teams typically call Kling V2.5 Turbo Pro Text-to-Video.

What you get when you call Kling V2.5 Turbo Pro Text-to-Video through LLM.API.

Unified AI Routing
Practical: Reach Kling V2.5 Turbo Pro Text-to-Video and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.
Cost Control
Practical: Compare provider price points and keep spend visible as you scale Kling V2.5 Turbo Pro Text-to-Video.
More performance, less spend.
Reliability Layer
Practical: 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 V2.5 Turbo Pro 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
Practical: Swap Kling V2.5 Turbo Pro 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 V2.5 Turbo Pro Text-to-Video)
You can tolerate longer generation times than chat (Kling V2.5 Turbo Pro Text-to-Video)
You need resolution-tiered pricing for motion content (Kling V2.5 Turbo Pro Text-to-Video)

Avoid if...

You require sub-second interactive generation
You only need still images or chat text
You need broadcast-length films or guaranteed cinema-grade continuity

LLM API rating for Kling V2.5 Turbo Pro Text-to-Video

★ 2.5/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & valueEstimated from published specs

2.5Production adoptionNot yet tracked — no public usage data for this release

2.8Benchmark qualityNo public Arena rank — scored on declared reasoning support

2.0Developer ecosystemContext window, tool and JSON support, price against the category median

How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

COMMUNITY

What creators say about AI video models

LMArena—Speed—Sources: LMArena, Artificial Analysis

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 V2.5 Turbo Pro 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 V2.5 Turbo Pro Text-to-Video

Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.

Developers on WaveSpeedAI report that the model excels at processing complex, multi-step instructions, allowing for precise control over sequential narrative scenes and causal relationships within generated videos.
Technical documentation highlights significant improvements in motion stability, with developers noting reduced artifacts such as jitter, tearing, and frame drops even during high-motion combat scenes.
In professional blind tests reported by platforms like WaveSpeedAI, the model significantly outperformed competitors like Veo and Seedance, achieving win-loss ratios of up to 285% in text-to-video tasks.

SOURCES

Frequently Asked Questions

How is Kling V2.5 Turbo Pro Text-to-Video priced on LLM.API?
Listed pricing metadata shows: $0.07/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
What are limitations of Kling V2.5 Turbo Pro Text-to-Video?
Like other API models, Kling V2.5 Turbo Pro Text-to-Video can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.
How long do Kling V2.5 Turbo Pro Text-to-Video jobs take?
Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.
Can I use tools or structured outputs with Kling V2.5 Turbo Pro Text-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
Which providers serve Kling V2.5 Turbo Pro Text-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
What is the context length for Kling V2.5 Turbo Pro Text-to-Video?
Reported context for Kling V2.5 Turbo Pro Text-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
What is Kling V2.5 Turbo Pro Text-to-Video?
Video generation model by Muapi. On LLM.API it is addressed as `kling-v2.5-turbo-pro-t2v`.
Does Kling V2.5 Turbo Pro Text-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.

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Kling V2.5 Turbo Pro Text-to-Video API: Endpoint & Pricing

What is Kling V2.5 Turbo Pro Text-to-Video?

Can you self-host Kling V2.5 Turbo Pro Text-to-Video?

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

Kling V2.5 Turbo Pro Text-to-Video in production

Product visualization

Text-to-video generation

Iterative creatives

Motion coherence

Resolution options

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth