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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.
💰Qwen: Qwen2.5 VL 32B Instruct is 59% cheaper than llama-guard-3-8b
⚡Qwen: Qwen2.5 VL 32B Instruct is 170ms faster than llama-guard-3-8b
Price (lower is better), Speed/Latency (lower is better), Performance (higher is better)
Qwen: Qwen2.5 VL 32B Instruct is 142% cheaper
| Spec | llama-guard-3-8b | Qwen: Qwen2.5 VL 32B Instruct |
|---|---|---|
| Provider | meta | qwen |
| Input price / 1M tokens | $0.48 | $0.20 |
| Output price / 1M tokens | $0.03 | $0.60 |
| Context window | 131k tokens | 128k tokens |
| Latency (p50) | 170ms | — |
| Best benchmark score | — | — |
| Open source | No | No |
Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.
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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