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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 38% cheaper than Google: Gemma 2 9B
⚡Google: Gemma 2 9B is 57ms faster than plamo-embedding-1b
Price (lower is better), Speed/Latency (lower is better), Performance (higher is better)
plamo-embedding-1b is 61% cheaper
| Spec | plamo-embedding-1b | Google: Gemma 2 9B |
|---|---|---|
| Provider | pfnet | |
| Input price / 1M tokens | $0.02 | $0.03 |
| Output price / 1M tokens | — | $0.09 |
| Context window | — | 8k 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.
Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class. Designed for a wide variety of...
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