并排比较最多4个AI模型的基准测试、价格、速度和功能。我们的LLM比较工具从300+个模型中提取实时数据，包括GPT-4o、Claude Opus、Gemini 2.5 Pro、DeepSeek R1和Llama 4。选择下方任意模型，查看它们在上下文窗口、输出定价、功能支持和综合评分方面的对比。
Wan AI
Composite Score
1/5 signal wins
Wan 2.1 T2V leads on 1/5 signals
| Signal | Wan 2.1 T2V | Delta | LTX-Video 2 |
|---|---|---|---|
Capabilities | 0 | -- | |
Pricing | 30 | -- | |
Context window size | 0 | -- | |
Recency | 57 | +3 | |
Output Capacity | 20 | -- | |
| Overall Result | 1 wins | of 5 | 0 wins |
Wan AI
Lightricks
Wan 2.1 T2V and LTX-Video 2 are extremely close in overall performance (only 1 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Wan 2.1 T2V
Marginally better benchmark scores; both are excellent
Best for Cost
Wan 2.1 T2V
0% lower pricing; better value at scale
Best for Reliability
Wan 2.1 T2V
Higher uptime and faster response speeds
Best for Prototyping
Wan 2.1 T2V
Stronger community support and better developer experience
Best for Production
Wan 2.1 T2V
Wider enterprise adoption and proven at scale
by Wan AI
Wan AI
Lightricks
| Metric | Wan 2.1 T2V | LTX-Video 2 | Veo 2 |
|---|---|---|---|
| Overall Score | 20 | 19 | 18 |
| Rank | 1 | 2 | 3 |
| Quality Rank | #1 | #2 | #3 |
| Adoption Rank | #1 | #2 | #3 |
| Status | |||
| Confidence | High confidence | High confidence | High confidence |
| Parameters | -- | -- | -- |
| Context Window | -- | -- | -- |
| Pricing | Free | Free | Free |
| Signal Scores | |||
| Capabilities | 0 | 0 | 0 |
| Pricing | 30 | 30 | 100 |
| Context window size | 0 | 0 | 0 |
| Recency | 57 | 54 | 49 |
| Output Capacity | 20 | 20 | 20 |
使用上方的比较工具选择最多4个AI模型。我们从基准测试、每百万令牌价格、上下文窗口大小、输出容量、功能（视觉、函数调用、推理）和综合评分等方面进行比较。数据每小时刷新。
关键指标包括：基准测试分数（MMLU、SWE-bench、Arena Elo）、定价（每百万令牌的输入和输出成本）、上下文窗口大小、输出令牌限制、延迟、功能（视觉、推理、函数调用、JSON模式），以及模型是否开源。
这取决于您的使用场景。GPT-4o在多模态任务中表现出色且拥有更大的生态系统，而Claude Opus在扩展推理和安全性方面领先。使用我们的工具直接比较它们，查看最新的基准测试分数和定价。