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Veo 3.1 Fast Text-to-Video

Veo 3.1 Fast Text-to-Video exposes video generation video generation through LLM.API so motion experiments share the same billing and auth as other models.

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What is Veo 3.1 Fast Text-to-Video?

Veo 3.1 Fast Text-to-Video is a generative video model available through LLM.API as `veo3.1-fast-t2v`. Video generation model by Muapi. Expect text prompts and video outputs, with pricing often tied to seconds and resolution.

Providers

LLM.API routes Veo 3.1 Fast Text-to-Video to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
muapi$0 in
$0 out

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

ProviderPricingContextCapabilities
muapi30% offin —; out $0.0975 per second of video——

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Veo 3.1 Fast Text-to-Video right here — free to start.

Veo 3.1 Fast Text-to-Video
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Suggestions for your first prompt

Code snippet

Call Veo 3.1 Fast Text-to-Video through the OpenAI-compatible API — Video generation via LLM.API (see docs for media endpoints).

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="veo3.1-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)
{
  "model": "veo3.1-fast-t2v",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Short-form content

    Fits vertical and horizontal short-form marketing formats. Relevant for `veo3.1-fast-t2v` workloads on LLM.API.

  • Cinematic prompting

    Responds to camera, lighting, and mood language in creative briefs. Reflects video generation positioning for this endpoint.

  • Product visualization

    Helps visualize products and environments before shoot or 3D work. Tuned to how teams typically call Veo 3.1 Fast Text-to-Video.

  • Motion coherence

    Targets temporally consistent motion across frames for the requested scene.

  • Resolution options

    Supports multiple output resolutions depending on provider pricing tiers.

6 Most Valuable Use Cases

  • Short promotional clips from written briefs with Veo 3.1 Fast Text-to-Video
  • Creative exploration for campaign storyboards
  • Scene tests for world and environment design with Veo 3.1 Fast Text-to-Video
  • UGC-style drafts for performance marketing
  • Localized motion variants of the same concept with Veo 3.1 Fast Text-to-Video
  • Social-first product teaser generation

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Veo 3.1 Fast Text-to-Video on LLM.API?

  • Unified AI Routing

    Production: Reach Veo 3.1 Fast Text-to-Video and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Practical: Compare provider price points and keep spend visible as you scale Veo 3.1 Fast Text-to-Video.

  • Reliability Layer

    Retry and route across configured providers when a single upstream blips.

  • Observability

    Production: Trace prompts, tokens, and errors for Veo 3.1 Fast Text-to-Video alongside the rest of your stack.

  • Drop-in SDKs

    Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Practical: Swap Veo 3.1 Fast Text-to-Video for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You can tolerate longer generation times than chat (Veo 3.1 Fast Text-to-Video)
  • You are building short-form generative video features (Veo 3.1 Fast Text-to-Video)
  • You need resolution-tiered pricing for motion content (Veo 3.1 Fast Text-to-Video)

Avoid if...

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

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 Veo 3.1 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

Frequently Asked Questions

  • Is Veo 3.1 Fast Text-to-Video a chat model?

    No—Veo 3.1 Fast Text-to-Video is categorized as a video model. Use the matching API surface rather than assuming chat completions.

  • What are limitations of Veo 3.1 Fast Text-to-Video?

    Like other API models, Veo 3.1 Fast 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 is Veo 3.1 Fast Text-to-Video priced on LLM.API?

    Listed pricing metadata shows: $0.098/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What is Veo 3.1 Fast Text-to-Video?

    Video generation model by Muapi. On LLM.API it is addressed as `veo3.1-fast-t2v`.

  • How do I call Veo 3.1 Fast Text-to-Video via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "veo3.1-fast-t2v" and your LLM.API key. See the code snippet on this page.

  • When should I choose Veo 3.1 Fast Text-to-Video?

    You are building short-form generative video features — especially when you specifically need Veo 3.1 Fast Text-to-Video.

  • Which providers serve Veo 3.1 Fast Text-to-Video?

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

  • What modalities does Veo 3.1 Fast Text-to-Video support?

    Veo 3.1 Fast Text-to-Video accepts text and produces video according to its architecture metadata on LLM.API.

  • Can I use tools or structured outputs with Veo 3.1 Fast Text-to-Video?

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

  • How long do Veo 3.1 Fast Text-to-Video jobs take?

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

  • Does Veo 3.1 Fast Text-to-Video support streaming?

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

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