ministral-3b
A compact, efficient model for on-device tasks like smart assistants and local analytics, offering low-latency performance.
| Provider | Source | Input Price ($/1M) | Output Price ($/1M) | Description | Free |
|---|---|---|---|---|---|
| vercel | vercel | Input: $0.04 | Output: $0.04 | A compact, efficient model for on-device tasks like smart assistants and local analytics, offering low-latency performance. | |
| githubmodels | models-dev | Input: $0.00 | Output: $0.00 | Provider: GitHub Models, Context: 128000, Output Limit: 8192 | |
| azure | models-dev | Input: $0.04 | Output: $0.04 | Provider: Azure, Context: 128000, Output Limit: 8192 | |
| azurecognitiveservices | models-dev | Input: $0.04 | Output: $0.04 | Provider: Azure Cognitive Services, Context: 128000, Output Limit: 8192 | |
| azureai | litellm | Input: $0.04 | Output: $0.04 | Source: azure_ai, Context: 128000 | |
| openrouter | openrouter | Input: $0.04 | Output: $0.04 | Ministral 3B is a 3B parameter model optimized for on-device and edge computing. It excels in knowledge, commonsense reasoning, and function-calling, outperforming larger models like Mistral 7B on most benchmarks. Supporting up to 128k context length, it’s ideal for orchestrating agentic workflows and specialist tasks with efficient inference. Context: 131072 |