LTX 2 Fast Image-to-Video API: Endpoint & Pricing
Create short generative video with LTX 2 Fast Image-to-Video on LLM.API, with resolution-aware pricing and a unified developer workflow.
What is LTX 2 Fast Image-to-Video?
LTX 2 Fast Image-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 LTX 2 Fast Image-to-Video?
No. We found no public weights for LTX 2 Fast 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.
Providers
LLM.API routes LTX 2 Fast Image-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 LTX 2 Fast Image-to-Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call LTX 2 Fast 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 ltx-2-fast-i2v 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": "ltx-2-fast-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="ltx-2-fast-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: "ltx-2-fast-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="ltx-2-fast-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": "ltx-2-fast-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 ltx-2-fast-i2v · 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.
LTX 2 Fast Image-to-Video in production
What the model is good at.
Motion coherence
Targets temporally consistent motion across frames for the requested scene. Tuned to how teams typically call LTX 2 Fast Image-to-Video.
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 LTX 2 Fast Image-to-Video.
Text-to-video generation
Synthesizes short video clips from prompts for ads, explainers, and social.
Storyboard acceleration
Turns written beats into moving drafts for rapid review.
What you get when you call LTX 2 Fast Image-to-Video through LLM.API.
Unified AI Routing
Reach LTX 2 Fast 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 LTX 2 Fast 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
Production: Trace prompts, tokens, and errors for LTX 2 Fast 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 LTX 2 Fast 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 can tolerate longer generation times than chat (LTX 2 Fast Image-to-Video)
- You need resolution-tiered pricing for motion content (LTX 2 Fast Image-to-Video)
- You are building short-form generative video features (LTX 2 Fast Image-to-Video)
Avoid if...
- You need broadcast-length films or guaranteed cinema-grade continuity
- You only need still images or chat text
- You require sub-second interactive generation
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 LTX 2 Fast 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 LTX 2 Fast Image-to-Video
Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.
- Developers on GitHub report difficulties achieving reasonable results using the Python scripts for image-to-video generation, specifically requesting correct parameter sets to improve the quality of their generated cinematic spell-clash scenes.
- A developer on Hugging Face reported a runtime error and library loading issues, specifically involving a missing 'libcudart.so.13' file when attempting to initialize the LTX-2 image-to-video pipeline.
SOURCES
Frequently Asked Questions
What is LTX 2 Fast Image-to-Video?
Video generation model by Muapi. On LLM.API it is addressed as `ltx-2-fast-i2v`.
How do I call LTX 2 Fast Image-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "ltx-2-fast-i2v" and your LLM.API key. See the code snippet on this page.
Where is the canonical page for LTX 2 Fast Image-to-Video?
https://llmapi.ai/models/ltx-2-fast-i2v/
Which providers serve LTX 2 Fast Image-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
Does LTX 2 Fast Image-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
How long do LTX 2 Fast Image-to-Video jobs take?
Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.
When should I choose LTX 2 Fast Image-to-Video?
You can tolerate longer generation times than chat — especially when you specifically need LTX 2 Fast Image-to-Video.
What is the context length for LTX 2 Fast Image-to-Video?
Reported context for LTX 2 Fast Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
Can I use tools or structured outputs with LTX 2 Fast Image-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
COMPARE
Competitive Models
Higgsfield Dop Image-to-Video
Output$0.06 / secondList price per second of video.
— in / $0.06 out per second of video, context varies — the closest current alternative to LTX 2 Fast Image-to-Video.
LTX 2 19B Text-to-Video
Output$0.06 / secondList price per second of video.
— in / $0.06 out per second of video, context varies — the closest current alternative to LTX 2 Fast Image-to-Video.
WAN 2.2 Text-to-Video
Output$0.06 / secondList price per second of video.
— in / $0.06 out per second of video, context varies — the closest current alternative to LTX 2 Fast Image-to-Video.
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