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Kling V2.1 Pro Image-to-Video API: Endpoint & Pricing

Kling V2.1 Pro Image-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 V2.1 Pro Image-to-Video?

Kling V2.1 Pro Image-to-Video is a generative video model available through LLM.API as `kling-v2.1-pro-i2v`. Video generation model by Muapi. Expect text, image prompts and video outputs, with pricing often tied to seconds and resolution.

Can you self-host Kling V2.1 Pro Image-to-Video?

No. We found no public weights for Kling V2.1 Pro Image-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.

Get API keySee API code ↓

Providers

LLM.API routes Kling V2.1 Pro Image-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.

ProviderPricingContextCapabilities
muapiin —; 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 V2.1 Pro Image-to-Video right here — free to start.

Kling V2.1 Pro Image-to-Video
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Kling V2.1 Pro Image-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-v2.1-pro-i2v 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-v2.1-pro-i2v",
    "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-v2.1-pro-i2v",
    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-v2.1-pro-i2v",
  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-v2.1-pro-i2v",
    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-v2.1-pro-i2v",
  "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-v2.1-pro-i2v · OpenAI-compatible.

  • POST /v1/chat/completionsChat Completions — supported
FeatureStatusHow to set it
Function calling (tools)Not supportedtools, tool_choice
Parallel tool callsNot supportedparallel_tool_calls
JSON modeNot supportedresponse_format: {"type": "json_object"}
Structured outputsNot supportedresponse_format: {"type": "json_schema", …}
StreamingNot supportedstream: true
Vision (image input)Not supportedimage_url content parts
Web searchNot supportedweb_search

ERRORS

Errors & fallback routing

CodeWhat it meansWhat to do
401Missing or invalid API key.Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active.
429Rate 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.
5xxUpstream 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 V2.1 Pro Image-to-Video in production

What the model is good at.

  • Motion coherence

    Targets temporally consistent motion across frames for the requested scene. Reflects video generation positioning for this endpoint.

  • Product visualization

    Helps visualize products and environments before shoot or 3D work. Relevant for `kling-v2.1-pro-i2v` workloads on LLM.API.

  • 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.

  • Short-form content

    Fits vertical and horizontal short-form marketing formats.

  • Iterative creatives

    Enables prompt-based A/B exploration of motion concepts. Tuned to how teams typically call Kling V2.1 Pro Image-to-Video.

What you get when you call Kling V2.1 Pro Image-to-Video through LLM.API.

  • Unified AI Routing

    Reach Kling V2.1 Pro Image-to-Video and sibling models through one OpenAI-compatible endpoint.

    One endpoint, every model.

  • Cost Control

    Compare provider price points and keep spend visible as you scale Kling V2.1 Pro Image-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 V2.1 Pro Image-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

    Production: Swap Kling V2.1 Pro Image-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 V2.1 Pro Image-to-Video)
  • You need resolution-tiered pricing for motion content (Kling V2.1 Pro Image-to-Video)
  • You can tolerate longer generation times than chat (Kling V2.1 Pro Image-to-Video)

Avoid if...

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

LLM API rating for Kling V2.1 Pro Image-to-Video

★ 2.6/ 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
3.1Benchmark qualityScored on multimodal input support and context
2.0Developer ecosystemContext window, tool and JSON support, price against the category median
Vision & multimodal 2.6
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:

  1. 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.
  2. 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.
  3. 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 V2.1 Pro Image-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 V2.1 Pro Image-to-Video

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

  • Developers on Rivya AI describe the model as a practical legacy choice for 'two-frame' shots, specifically when the primary goal is transitioning between a defined start and an optional end frame.
  • Technical documentation from Eachlabs and AI.cc notes the Pro variant provides a middle-tier quality ladder, offering sharper visuals and smoother camera movements compared to the Standard version.
  • Developers utilizing the API via GPT Proto and Lumereel highlight the model's ability to maintain visual identity and texture consistency across 5 to 10-second clips for professional-grade storytelling.

SOURCES

Frequently Asked Questions

  • What is the context length for Kling V2.1 Pro Image-to-Video?

    Reported context for Kling V2.1 Pro Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.

  • Does Kling V2.1 Pro Image-to-Video support streaming?

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

  • How long do Kling V2.1 Pro Image-to-Video jobs take?

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

  • What is Kling V2.1 Pro Image-to-Video?

    Video generation model by Muapi. On LLM.API it is addressed as `kling-v2.1-pro-i2v`.

  • What are limitations of Kling V2.1 Pro Image-to-Video?

    Like other API models, Kling V2.1 Pro Image-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.

  • When should I choose Kling V2.1 Pro Image-to-Video?

    You are building short-form generative video features — especially when you specifically need Kling V2.1 Pro Image-to-Video.

  • Can I use tools or structured outputs with Kling V2.1 Pro Image-to-Video?

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

  • Where is the canonical page for Kling V2.1 Pro Image-to-Video?

    https://llmapi.ai/models/kling-v2-1-pro-i2v/

  • What modalities does Kling V2.1 Pro Image-to-Video support?

    Kling V2.1 Pro Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.

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