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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.
💰embeddinggemma-300m is 100% cheaper than Qwen: Qwen2.5 VL 32B Instruct
⚡Qwen: Qwen2.5 VL 32B Instruct is 45ms faster than embeddinggemma-300m
Price (lower is better), Speed/Latency (lower is better), Performance (higher is better)
embeddinggemma-300m is Infinity% cheaper
| Spec | embeddinggemma-300m | Qwen: Qwen2.5 VL 32B Instruct |
|---|---|---|
| Provider | qwen | |
| Input price / 1M tokens | Free | $0.20 |
| Output price / 1M tokens | — | $0.60 |
| Context window | — | 128k tokens |
| Latency (p50) | 45ms | — |
| Best benchmark score | — | — |
| Open source | No | No |
EmbeddingGemma is a 300M parameter, state-of-the-art for its size, open embedding model from Google, built from Gemma 3 (with T5Gemma initialization) and the same research and technology used to create Gemini models. EmbeddingGemma produces vector representations of text, making it well-suited for search and retrieval tasks, including classification, clustering, and semantic similarity search. This model was trained with data in 100+ spoken languages.
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...
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