SWEN Video Registry

Best AI Video Models 2026Text-to-Video and Image-to-Video

This page now uses a canonical video registry. The score evaluates visual quality, speed, control, value and API readiness for real video-generation stacks.

6

canonical products ranked

5

with public API or developer access

6

with programmable workflows or API creation

1 · Top Score
Sora 2
OpenAIOpenAI
95.1

OpenAI frontier video model focused on realism, controllability and synchronized dialogue plus sound effects.

text-to-videoText to VideoAPI
2 · Top Score
94.4

Runway flagship video model with very high fidelity and strong creative control for professional visual teams.

image-to-videoImage to VideoAPI
3 · Top Score
92.8

Luma flagship video model emphasizing directability, continuity and scalable API-driven creative workflows.

text-to-videoText to VideoAPI

Full Ranking

Composite score built from visual quality, speed, control, value and API readiness.

0 open source
#ModelScorePrice
1Sora 2
OpenAI frontier video model focused on realism, controllability and synchronized dialogue plus sound effects.
95.1API + app access
2Runway Gen-4.5
Runway flagship video model with very high fidelity and strong creative control for professional visual teams.
94.4Subscription + API workflows
3Luma Ray3.2
Luma flagship video model emphasizing directability, continuity and scalable API-driven creative workflows.
92.8Build with API
4Hailuo 2.3
MiniMax flagship video line building on Hailuo 02 with stronger motion, physical action and more stable visuals.
91.7API points model
5Kling 2.1
Kling flagship lineup for high-quality creator-facing video generation with strong output fidelity and increasingly production-grade resolution.
90.1App subscription / credits
6Pika 2.5
Pika consumer-friendly video stack focused on fast creative iteration, effects and playful media workflows.
87.9Credits-based plans via app / Fal

Score Breakdown

Qualitytop model reference
Speedtop model reference
Controltop model reference

FAQ

Why is the video ranking more trustworthy now?

Because it no longer depends on stale `ai_models.tipo = video` rows only. The page now reads from the SWEN Video Registry, which is refreshed by the universal benchmark sync pipeline.

What is the main ranking bias here?

The ranking is intentionally product-oriented. Quality matters, but public API access, controllability and operational readiness also matter, so a beautiful closed app can still lose to a slightly weaker but programmable stack.

Does this replace image-model sync from Artificial Analysis?

No. Video is now its own vertical. It no longer borrows LLM data or waits for unrelated syncs to refresh.

BenchmarkCodeImageAudioVideoAgents