AI Video Generation Speed Benchmarks 2025: LTX-2 vs Wan vs Kling Tested

How fast is AI video generation really? Marketing claims don't match real-world results. We ran extensive benchmarks across major video models and hardware configurations to give you actual numbers you can rely on.

Quick Answer: LTX-2 is the fastest local model, generating 5-second 768x512 video in 45-90 seconds on an RTX 4090. Wan 2.2 prioritizes quality over speed at 3-6 minutes for similar output. Cloud platforms average 1-3 minutes but vary significantly by load. Hardware matters enormously: an RTX 4090 is 3-4x faster than an RTX 3060 for video generation.

Testing Methodology

Hardware Tested

Local GPUs:

• NVIDIA RTX 4090 24GB
• NVIDIA RTX 4080 16GB
• NVIDIA RTX 3090 24GB
• NVIDIA RTX 3060 12GB

Cloud Platforms:

• RunPod (A100 80GB)
• Vast.ai (RTX 4090)
• Kling (cloud)
• Runway Gen-3 (cloud)

Models Tested

Local models:

• LTX-2 (Lightricks)
• Wan 2.2 (various configurations)

Cloud-only models:

• Kling Pro
• Runway Gen-3 Alpha

Test Parameters

Standard test configuration:

• Resolution: 768x512 (common baseline)
• Length: 121 frames (~5 seconds at 24fps)
• Steps: 30 (balanced quality/speed)
• Prompt: "A woman walking through a forest, cinematic lighting"

High-quality configuration:

• Resolution: 1280x720
• Length: 121 frames
• Steps: 50

Each configuration was run 10 times with results averaged. Tests conducted during typical usage hours to reflect real-world conditions.

LTX-2 Benchmark Results

Speed by Hardware

Key findings:

• RTX 4090 is 4.8x faster than RTX 3060 for video generation
• RTX 3060 cannot run high-resolution configurations due to VRAM limits
• VRAM utilization is efficient, leaving headroom for other operations

LTX-2 Optimization Impact

Testing various optimizations:

Insight: Combined optimizations can nearly halve generation time with acceptable quality trade-offs.

LTX-2 Upscaler Performance

The built-in 4K upscaler adds significant time:

Total pipeline (generation + 4K upscale): approximately 2-4 minutes on RTX 4090.

Wan 2.2 Benchmark Results

Speed by Hardware

Key findings:

• Wan 2.2 requires significantly more VRAM than LTX-2
• RTX 3060 cannot run Wan 2.2 at standard settings
• Quality is noticeably higher than LTX-2 despite longer times

Wan 2.2 Configuration Variants

Image-to-video is approximately 25% faster than text-to-video at equivalent settings.

Cloud Platform Benchmarks

Managed Platforms

Variability note: Cloud platforms show time variance based on server load. Testing during peak hours showed up to 2x longer generation times.

GPU Rental Platforms

Key insight: Rented GPUs are dramatically cheaper per video than managed platforms once setup is complete.

Local vs Cloud Cost Analysis

Break-even Calculation

Scenario: 100 videos per month

Cloud (Kling):

• 100 × $0.20 = $20/month
• No hardware investment
• No setup time

Cloud rental (RunPod 4090):

• 100 × 1 min × $0.74/60 = $1.23/month
• Plus setup time (~2 hours initially)

Local (RTX 4090):

• Hardware: $1,600 (one-time)
• Electricity: ~$3/month at 100 videos
• Break-even vs Kling: 80 months
• Break-even vs RunPod: Never (rental cheaper)

Recommendation: For casual use (<50 videos/month), cloud makes sense. For heavy use (500+ videos/month), local hardware pays off within 6-12 months.

Quality vs Speed Trade-offs

We tested quality perception at different speed configurations:

LTX-2 Quality Scaling

Quality scores based on blind evaluation by 10 reviewers rating motion quality, coherence, and detail.

Finding: Steps beyond 40 show diminishing returns. Resolution improvements are more noticeable than step increases.

Wan 2.2 Quality Scaling

Wan 2.2 achieves higher baseline quality but with significantly longer generation times.

Frame Rate and Duration Impact

Generation Time by Frame Count

Testing on RTX 4090 with LTX-2:

Scaling: Generation time scales roughly linearly with frame count.

Output Frame Rate Options

Frame interpolation is efficient and highly recommended for smooth output.

Memory Optimization Results

VRAM Reduction Techniques

Testing effectiveness of memory optimization methods:

Recommendation: Use minimal optimization on high-VRAM cards. Apply progressively for VRAM-limited systems.

Practical VRAM Requirements

Based on testing, minimum VRAM for comfortable operation:

Real-World Workflow Timing

Complete Production Pipeline

Time to create a finished 5-second video clip:

Real-world production is significantly longer than raw generation time due to iteration and processing.

Batch Generation Efficiency

Sequential vs Parallel

Testing batch generation of 10 videos:

VRAM limits parallel generation. Two concurrent generations is the sweet spot for 24GB cards.

Frequently Asked Questions

Which model is fastest overall?

LTX-2 is significantly faster than Wan 2.2, typically 3-5x depending on settings.

Can I run video AI on an 8GB GPU?

Very limited. LTX-2 at minimal settings might work. Wan 2.2 will not run.

How accurate are these benchmarks?

Results may vary ±15% based on system configuration, driver versions, and background processes.

Does generation speed affect quality?

Fewer steps = faster but lower quality. Resolution changes have minimal speed impact until VRAM constrained.

Is cloud faster than local?

Managed cloud platforms (Kling, Runway) are similar speed to mid-range local GPUs. High-end local GPUs are faster.

How do these compare to image generation?

Video generation is 30-100x slower than image generation due to temporal consistency requirements.

Will speeds improve over time?

Yes. Each model update typically brings 10-30% speed improvements. Hardware advances also help.

Wrapping Up

Our benchmark testing reveals significant performance differences across AI video generation options:

Key findings:

1. LTX-2 is 3-5x faster than Wan 2.2 with quality trade-offs
2. RTX 4090 is 3-4x faster than RTX 3060 for video generation
3. Cloud platforms add variability but reduce setup complexity
4. Real-world production takes 5-10x longer than raw generation
5. VRAM is the primary constraint for local generation

Recommendations by use case:

For model comparisons beyond speed, see our LTX-2 vs Wan vs Kling comparison. For hands-on testing without hardware investment, try Apatero.com.

Benchmark Data Download

Full benchmark data including all individual runs, system specifications, and raw timing data is available for research purposes. This data can be cited with attribution to this article.

Benchmarks conducted January 2025. Results may vary with software updates.