LTX 2 Fast Text-to-Video API: Endpoint & Pricing
Create short generative video with LTX 2 Fast Text-to-Video on LLM.API, with resolution-aware pricing and a unified developer workflow.
What is LTX 2 Fast Text-to-Video?
LTX 2 Fast 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 LTX 2 Fast Text-to-Video?
No. We found no public weights for LTX 2 Fast 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 Fast 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 Fast Text-to-Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call LTX 2 Fast 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-fast-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-fast-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-fast-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-fast-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-fast-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-fast-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-fast-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 Fast Text-to-Video in production
What the model is good at.
Motion coherence
Targets temporally consistent motion across frames for the requested scene. Relevant for `ltx-2-fast-t2v` workloads on LLM.API.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Tuned to how teams typically call LTX 2 Fast Text-to-Video.
Cinematic prompting
Responds to camera, lighting, and mood language in creative briefs. Grounded in the model's video role rather than generic chat claims.
Short-form content
Fits vertical and horizontal short-form marketing formats. Tuned to how teams typically call LTX 2 Fast Text-to-Video.
Text-to-video generation
Synthesizes short video clips from prompts for ads, explainers, and social.
What you get when you call LTX 2 Fast Text-to-Video through LLM.API.
Unified AI Routing
Production: Reach LTX 2 Fast 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 LTX 2 Fast Text-to-Video.
More performance, less spend.Reliability Layer
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 Fast 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 Fast 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 can tolerate longer generation times than chat (LTX 2 Fast Text-to-Video)
- You are building short-form generative video features (LTX 2 Fast Text-to-Video)
- You need resolution-tiered pricing for motion content (LTX 2 Fast 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 Fast 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 Fast Text-to-Video
Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.
- Developers on Reddit have observed technical hurdles with the image-to-video capabilities, specifically reporting issues where the model generates only a single frame instead of a full video sequence.
- Developers in the open-source community indicate that the 'Fast' variant is preferred for iterative workflows and rapid prototyping due to its significant speed advantages over full-fidelity versions.
- In local development discussions, users have inquired about installation procedures for the distilled real-time versions, noting that these smaller variants are ideal for systems with limited VRAM.
SOURCES
Frequently Asked Questions
Can I use tools or structured outputs with LTX 2 Fast Text-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
What is LTX 2 Fast Text-to-Video?
Video generation model by Muapi. On LLM.API it is addressed as `ltx-2-fast-t2v`.
How long do LTX 2 Fast Text-to-Video jobs take?
Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.
Where is the canonical page for LTX 2 Fast Text-to-Video?
https://llmapi.ai/models/ltx-2-fast-t2v/
How do I call LTX 2 Fast Text-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "ltx-2-fast-t2v" and your LLM.API key. See the code snippet on this page.
When should I choose LTX 2 Fast Text-to-Video?
You can tolerate longer generation times than chat — especially when you specifically need LTX 2 Fast Text-to-Video.
What is the context length for LTX 2 Fast Text-to-Video?
Reported context for LTX 2 Fast Text-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
How is LTX 2 Fast Text-to-Video priced on LLM.API?
Listed pricing metadata shows: 1080p: $0.06/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
Does LTX 2 Fast 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 Fast Text-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
What modalities does LTX 2 Fast Text-to-Video support?
LTX 2 Fast Text-to-Video accepts text and produces video according to its architecture metadata on LLM.API.
Is LTX 2 Fast Text-to-Video a chat model?
No—LTX 2 Fast Text-to-Video is categorized as a video model. Use the matching API surface rather than assuming chat completions.
COMPARE
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LTX 2 19B Text-to-Video
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