LTX 2 Pro Text-to-Video API: Endpoint & Pricing
Create short generative video with LTX 2 Pro Text-to-Video on LLM.API, with resolution-aware pricing and a unified developer workflow.
What is LTX 2 Pro Text-to-Video?
LTX 2 Pro Text-to-Video is a generative video model available through LLM.API as `ltx-2-pro-t2v`. Video generation model by Muapi. Expect text prompts and video outputs, with pricing often tied to seconds and resolution.
Can you self-host LTX 2 Pro Text-to-Video?
No. We found no public weights for LTX 2 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, with custom volume discounts on request.
Providers
LLM.API routes LTX 2 Pro 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 LTX 2 Pro Text-to-Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call LTX 2 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 ltx-2-pro-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": "ltx-2-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="ltx-2-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: "ltx-2-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="ltx-2-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": "ltx-2-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 ltx-2-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.
LTX 2 Pro 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 LTX 2 Pro Text-to-Video.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Relevant for `ltx-2-pro-t2v` workloads on LLM.API.
Cinematic prompting
Responds to camera, lighting, and mood language in creative briefs. Tuned to how teams typically call LTX 2 Pro Text-to-Video.
Resolution options
Supports multiple output resolutions depending on provider pricing tiers. Grounded in the model's video role rather than generic chat claims.
Storyboard acceleration
Turns written beats into moving drafts for rapid review. Tuned to how teams typically call LTX 2 Pro Text-to-Video.
What you get when you call LTX 2 Pro Text-to-Video through LLM.API.
Unified AI Routing
Production: Reach LTX 2 Pro Text-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 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
Trace prompts, tokens, and errors for LTX 2 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
Production: Swap LTX 2 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 need resolution-tiered pricing for motion content (LTX 2 Pro Text-to-Video)
- You can tolerate longer generation times than chat (LTX 2 Pro Text-to-Video)
- You are building short-form generative video features (LTX 2 Pro Text-to-Video)
Avoid if...
- You only need still images or chat text
- You require sub-second interactive generation
- You need broadcast-length films or guaranteed cinema-grade continuity
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 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 LTX 2 Pro Text-to-Video
Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.
- Developers on Reddit and technical blogs highlight the model's native audio-video synchronization, which generates motion, dialogue, and ambience simultaneously in a single cohesive process to eliminate manual post-production matching.
- Technical users note that the model supports high-resolution outputs up to 4K (2160p) and features precise camera motion controls, including specific instructions for jib, dolly, and focus shift effects.
- Developers reporting on community forums observe that while the model excels at temporal consistency, some early versions experienced issues where Image-to-Video generation would occasionally output only a single frame.
SOURCES
Frequently Asked Questions
Is LTX 2 Pro Text-to-Video a chat model?
No—LTX 2 Pro Text-to-Video is categorized as a video model. Use the matching API surface rather than assuming chat completions.
When should I choose LTX 2 Pro Text-to-Video?
You can tolerate longer generation times than chat — especially when you specifically need LTX 2 Pro Text-to-Video.
How is LTX 2 Pro 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.
What is the context length for LTX 2 Pro Text-to-Video?
Reported context for LTX 2 Pro Text-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
What modalities does LTX 2 Pro Text-to-Video support?
LTX 2 Pro Text-to-Video accepts text and produces video according to its architecture metadata on LLM.API.
How do I call LTX 2 Pro Text-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "ltx-2-pro-t2v" and your LLM.API key. See the code snippet on this page.
What are limitations of LTX 2 Pro Text-to-Video?
Like other API models, LTX 2 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.
Does LTX 2 Pro Text-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
Which providers serve LTX 2 Pro Text-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
Where is the canonical page for LTX 2 Pro Text-to-Video?
https://llmapi.ai/models/ltx-2-pro-t2v/
Can I use tools or structured outputs with LTX 2 Pro Text-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
How long do LTX 2 Pro Text-to-Video jobs take?
Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.
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