7 best text-to-video APIs: models, queues & avatars

This guide uses first-party API documentation checked September 13, 2026. Magic Hour publishes the article and is included. We did not run a retained six-provider benchmark, so it does not claim one universal quality, speed or price winner.

Magic Hour publishes this guide and includes its own product in the comparison. Treat the recommendations as editorial guidance from a vendor, and verify the linked first-party product details and your own output requirements before choosing a tool.

Best text-to-video APIs at a glance

1. fal.ai: broad hosted model access

fal.ai’s current video API reference lists text-to-video, image-to-video and video-to-video endpoints across many underlying providers. Model pages expose their own input schema and price, while fal supports direct calls, queue-backed subscribe or submit flows and webhooks.

Choose fal.ai when a product needs to evaluate or route among several models without operating each stack. Name the exact endpoint in every log and comparison. A result from Kling, Seedance, Veo or another model hosted by fal should not be attributed to fal as if fal were the model.

2. Magic Hour: text-to-video beside related creative APIs

Magic Hour’s Text-to-Video API accepts a prompt plus supported model, duration, aspect ratio, resolution and audio settings. It returns a project ID and an estimated credit charge that is updated after completion; failed generation is documented as refunded.

Choose it when text-to-video must work beside image-to-video, image generation, editing, face swap, lip sync or other media operations. Save the selected model, submitted settings, project ID, status sequence, final credit charge and downloaded output.

3. Google Veo: direct Veo 3.1 access

Google’s Veo 3.1 API guide documents text and image inputs, native audio, landscape and portrait output, first and last frames, up to three reference images on supported variants and extension of eligible Veo-generated clips.

Veo is an asynchronous operation: submit, poll and then download. The exact model ID determines whether access is preview or stable and which duration, resolution and controls apply. Google also limits file storage and extension inputs; copy required outputs into your own governed storage before they expire.

4. Runway Dev: generation, editing and model routing

Runway Dev’s current model catalog exposes several text-, image- and video-based models alongside Runway generation and editing products. The current catalog includes Gen-4.5, Aleph 2, Seedance, H3, Veo and other routes, plus a model router.

Choose it when the API workflow needs both generation and subsequent video operations. Specify the model and endpoint rather than saying “the Runway API.” Record task IDs, input delivery, output format, status, credit usage and cancellation or deletion behavior.

5. Luma Agents: Ray 3.2 through one async surface

Luma Agents API exposes Ray 3.2 for text-to-video, image-to-video, multi-keyframe guidance, video editing and reframing. Its current quickstart uses one asynchronous generation endpoint followed by status polling and a presigned output download.

Choose it when the Ray 3.2 workflow and its create, edit or reframe types fit the product. Check duration, resolution, aspect ratio, source delivery and whether shared pay-as-you-go capacity or provisioned throughput matches the required reliability.

6. Synthesia: scripted presenter video

Synthesia’s Create Video API creates multi-clip videos inside a Synthesia account with aspect ratio, scene input, optional callback ID, visibility and a test mode. This is a structured avatar or template workflow, not an open-ended cinematic text-to-video model.

Choose it when the product needs a repeatable presenter, training or localized communication format. Verify avatar and voice authorization, script pronunciation, language review, template ownership, quota, callback mapping and private download lifetime.

7. MUAPI: multiple generative AI models

MUAPI is a unified AI API platform that lets developers access video, image, audio and LLM models through one API. With support for popular video models like Seedance, Veo and Kling, MUAPI makes it easier to build and scale AI-powered creative workflows.

Choose MUAPI when you need to experiment with multiple AI models without managing separate integrations. Its pay-as-you-go pricing, webhooks and polling support make it a practical option for testing and deploying generative AI applications.

Choose the API type before the provider

• Open-ended model generation. Use fal.ai, Google Veo, Runway Dev, Luma Agents or Magic Hour when a prompt should create a new visual shot.
• Image-led generation. Start from an approved frame when subject, composition or product appearance should be anchored. Confirm the selected endpoint accepts it.
• Video editing or transformation. Use a video-to-video or editing endpoint when real footage must remain the source. Do not send it to text-to-video and expect preservation.
• Avatar or presenter video. Use Synthesia or another authorized presenter API when the output is a scripted speaker. Compare it separately from cinematic generation.
• Multi-model platform. Use a host such as fal.ai, Runway Dev or Magic Hour when operational simplicity and model choice matter, but keep model-level records.

A reproducible video API evaluation

• Freeze four production shots. Include a person, product, motion-heavy scene and text or interface-sensitive scene. Add one avatar script only if presenter video is in scope.
• Normalize the deliverable. Match duration, aspect ratio, resolution and audio as closely as the endpoints permit. Document any mismatch.
• Retain every attempt. Save provider, endpoint, model, request, assets, settings, dates, status transitions, outputs and error responses.
• Score acceptance. Check prompt adherence, identity, product geometry, motion, text, camera, audio, policy fit and correction time.
• Measure operations. Record queue time, generation time, failure rate, rate limits, cancellation, retries, webhooks and output retrieval. Our 30-day Magic Hour API latency benchmark shows how to publish p50 end-to-end time, dates and sample sizes while keeping successful-job latency separate from reliability and creative acceptance.
• Calculate full cost. Include every billed attempt, storage, egress, staff review, correction and editing before dividing by approved clips.

Production integration checklist

• Separate development and production keys, permissions and spend limits.
• Validate files, URLs, MIME types, dimensions, duration and prompt size before submission.
• Persist your own job ID beside the provider task or project ID.
• Make retry and webhook handling idempotent so a callback cannot duplicate a customer job.
• Treat queued, running, completed, failed, blocked, canceled and expired as distinct states.
• Copy required outputs before signed URLs or provider retention windows expire.
• Pin model versions where supported and maintain a retained regression set for upgrades.
• Review upload rights, likeness and voice consent, commercial terms and disclosure obligations.

How to compare price and reliability

Cost per accepted clip = all generation charges + failed or rejected attempts + storage and egress + review, correction and finishing, divided by approved clips.

A per-second rate, platform credit and avatar minute are different units. Use the live price for the exact endpoint and settings. Report both submitted-job failure rate and creative rejection rate: a technically completed video can still fail the brief.

Related guides

For image and video APIs together, use the AI media API comparison. For image-led video, see best image-to-video APIs. For creator-facing platforms, use the best AI video generators.

For a small proof-of-concept stack, see the six-API weekend SaaS guide.