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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 Qwen: Qwen2.5 Coder 7B Instruct
⚡Qwen: Qwen2.5 Coder 7B 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 61% cheaper
| Spec | plamo-embedding-1b | Qwen: Qwen2.5 Coder 7B Instruct |
|---|---|---|
| Provider | pfnet | qwen |
| Input price / 1M tokens | $0.02 | $0.03 |
| Output price / 1M tokens | — | $0.09 |
| Context window | — | 33k 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-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE,...
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