| Signal | Runway Gen-3 Alpha | Delta | Stable Video Diffusion |
|---|---|---|---|
Capabilities | 0 | -- | |
Benchmarks | 17 | +17 | |
Pricing | 100 | -- | |
Context window size | 0 | -- | |
Recency | 7 | +7 | |
Output Capacity | 20 | -- | |
| Overall Result | 2 wins | of 6 | 0 wins |
Score History
11.3
current score
Runway Gen-3 Alpha
right now
3
current score
Runway
Stability AI
| Metric | Runway Gen-3 Alpha | Stable Video Diffusion | Winner |
|---|---|---|---|
| Overall Score | 11 | 3 | Runway Gen-3 Alpha |
| Rank | #6 | #10 | Runway Gen-3 Alpha |
| Quality Rank | #6 | #10 | Runway Gen-3 Alpha |
| Adoption Rank | #6 | #10 | Runway Gen-3 Alpha |
| Parameters | -- | -- | -- |
| Context Window | -- | -- | -- |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 0 | 0 | Runway Gen-3 Alpha |
| Benchmarks | 17 | -- | Runway Gen-3 Alpha |
| Pricing | 100 | 100 | Runway Gen-3 Alpha |
| Context window size | 0 | 0 | Runway Gen-3 Alpha |
| Recency | 7 | 0 | Runway Gen-3 Alpha |
| Output Capacity | 20 | 20 | Runway Gen-3 Alpha |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 11/100 (rank #6), placing it in the top 98% of all 290 models tracked.
Scores 3/100 (rank #10), placing it in the top 97% of all 290 models tracked.
Runway Gen-3 Alpha has a 8-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Runway Gen-3 Alpha also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (0K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (11/100) correlates with better nuance, coherence, and style in long-form content
Runway Gen-3 Alpha has a moderate advantage with a 8.3-point lead in composite score. It wins on more signal dimensions, but Stable Video Diffusion has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Runway Gen-3 Alpha
Marginally better benchmark scores; both are excellent
Best for Cost
Runway Gen-3 Alpha
0% lower pricing; better value at scale
Best for Reliability
Runway Gen-3 Alpha
Higher uptime and faster response speeds
Best for Prototyping
Runway Gen-3 Alpha
Stronger community support and better developer experience
Best for Production
Runway Gen-3 Alpha
Wider enterprise adoption and proven at scale
by Runway
| Capability | Runway Gen-3 Alpha | Stable Video Diffusion |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Runway
Stability AI
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Runway Gen-3 Alpha | Stable Video Diffusion |
|---|---|---|
| Context Window | -- | -- |
| Max Output Tokens | -- | -- |
| Open Source | No | Yes |
| Created | Jun 17, 2024 | Nov 21, 2023 |
The identical 10/100 scores likely reflect limitations in current video generation benchmarking, where both models hit similar quality thresholds on standard metrics. However, Gen-3 Alpha's #3 ranking versus Stable Video Diffusion's #7 suggests real-world performance differences not captured in automated scoring, potentially in areas like temporal consistency, motion quality, or adherence to text prompts that require human evaluation.
This fundamental difference makes them complementary rather than competitive: Gen-3 Alpha's text-to-video modality enables rapid prototyping from scripts while Stable Video Diffusion's image-to-video approach excels at animating existing storyboards or concept art. With both showing $0 pricing data and 0 token limits in the comparison, the real cost consideration becomes workflow integration rather than per-request pricing.
Stable Video Diffusion's open source nature allows for on-premise deployment and custom fine-tuning, critical for teams with proprietary visual styles or data privacy requirements. However, teams already using Runway's ecosystem benefit from Gen-3 Alpha's integration with their existing video editing tools, and its #3 ranking suggests performance advantages that may outweigh the flexibility of self-hosting.
The 0 token values indicate these video models don't use traditional text token metrics, making standard LLM comparison frameworks inadequate. Instead, teams should focus on video-specific constraints: Gen-3 Alpha typically generates 5-10 second clips at 720p-1080p resolution, while Stable Video Diffusion produces 2-4 second sequences from single images at similar resolutions.
Stable Video Diffusion's image-to-video modality provides deterministic control over the first frame, crucial for maintaining brand consistency or matching specific visual references. Combined with its open source nature allowing unlimited local generation versus potential API rate limits, teams prioritizing control and predictability over the marginal quality improvements suggested by Gen-3 Alpha's #3 vs #7 ranking may find Stable Video Diffusion more practical.