Loading...
Loading...
Side-by-side comparison of API pricing, context window, latency, and benchmark performance. Data refreshed daily from provider APIs and ModelStop's own latency probes.
💰plamo-embedding-1b is 91% cheaper than Qwen: Qwen2.5 VL 32B Instruct
⚡Qwen: Qwen2.5 VL 32B Instruct is 57ms faster than plamo-embedding-1b
Price (lower is better), Speed/Latency (lower is better), Performance (higher is better)
plamo-embedding-1b is 975% cheaper
| Spec | plamo-embedding-1b | Qwen: Qwen2.5 VL 32B Instruct |
|---|---|---|
| Provider | pfnet | qwen |
| Input price / 1M tokens | $0.02 | $0.20 |
| Output price / 1M tokens | — | $0.60 |
| Context window | — | 128k tokens |
| Latency (p50) | 57ms | — |
| Best benchmark score | — | — |
| Open source | No | No |
PLaMo-Embedding-1B is a Japanese text embedding model developed by Preferred Networks, Inc. It can convert Japanese text input into numerical vectors and can be used for a wide range of applications, including information retrieval, text classification, and clustering.
Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual...
Want to swap in a different model or estimate monthly costs?