| Signal | Sora | Delta | Wan 2.1 T2V |
|---|---|---|---|
Capabilities | 0 | -- | |
Pricing | 0 | -30 | |
Context window size | 0 | -- | |
Recency | 49 | -10 | |
Output Capacity | 20 | -- | |
| Overall Result | 0 wins | of 5 | 2 wins |
5
days ranked higher
0
days
25
days ranked higher
OpenAI
Wan AI
| Metric | Sora | Wan 2.1 T2V | Winner |
|---|---|---|---|
| Overall Score | 13 | 15 | Wan 2.1 T2V |
| Rank | #4 | #1 | Wan 2.1 T2V |
| Quality Rank | #4 | #1 | Wan 2.1 T2V |
| Adoption Rank | #4 | #1 | Wan 2.1 T2V |
| Parameters | -- | -- | -- |
| Context Window | -- | -- | -- |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 0 | 0 | Sora |
| Pricing | 0 | 30 | Wan 2.1 T2V |
| Context window size | 0 | 0 | Sora |
| Recency | 49 | 59 | Wan 2.1 T2V |
| Output Capacity | 20 | 20 | Sora |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 13/100 (rank #4), placing it in the top 99% of all 290 models tracked.
Scores 15/100 (rank #1), placing it in the top 100% of all 290 models tracked.
With only a 2-point gap, these models are in the same performance tier. The practical difference in output quality is minimal — your choice should depend on pricing, latency requirements, and specific feature needs.
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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Sora 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 (15/100) correlates with better nuance, coherence, and style in long-form content
Sora and Wan 2.1 T2V are extremely close in overall performance (only 2 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Sora
Marginally better benchmark scores; both are excellent
Best for Cost
Sora
0% lower pricing; better value at scale
Best for Reliability
Sora
Higher uptime and faster response speeds
Best for Prototyping
Sora
Stronger community support and better developer experience
Best for Production
Sora
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | Sora | Wan 2.1 T2V |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Wan AI
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Sora | Wan 2.1 T2V |
|---|---|---|
| Context Window | -- | -- |
| Max Output Tokens | -- | -- |
| Open Source | No | Yes |
| Created | Dec 9, 2024 | Feb 1, 2025 |
Wan 2.1 T2V scores 15/100 (rank #1) compared to Sora's 13/100 (rank #4), giving it a 2-point advantage. Wan 2.1 T2V is the stronger overall choice, though Sora may excel in specific areas like certain benchmarks.
Sora is ranked #4 and Wan 2.1 T2V is ranked #1 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Sora is cheaper at $0.00/M output tokens vs Wan 2.1 T2V's $0.00/M output tokens — a significant difference. Input token pricing: Sora at $0.00/M vs Wan 2.1 T2V at $0.00/M.
Context window information is available on the individual model pages.