Run Ministral-3-3B on Qualcomm NPU with NexaSDK and turbo optimization.
Quickstart
Install nexaSDK and create a free account at sdk.nexa.ai
Activate your device with your access token:
nexa config set license '<access_token>'
Run the model locally in one line:
nexa infer NexaAI/Ministral-3-3B-turbo-npu
Model Description
Ministral-3-3B-Instruct-2512 is the instruction-tuned variant of Mistral AI’s smallest Ministral 3 model: a compact multimodal language model combining a ~3.4B-parameter language core with a 0.4B-parameter vision encoder.
It is post-trained in FP8 for instruction-following, making it well-suited for chat-style agents, tool use, and grounded reasoning on both text and images.
With a large 256k context window and efficient edge-oriented design, it targets real-time use on GPUs and other resource-constrained hardware.
Features
Multimodal (vision + text): Understands and reasons over images alongside text in a single conversation.
Instruction-tuned: Optimized for following natural-language instructions, chat, and assistant-style workflows.
Agentic capabilities: Native support for function calling and structured JSON-style outputs for tool and API orchestration.
Large context window: Up to 256k tokens for long documents, multi-step workflows, and complex sessions.
Edge-optimized FP8 weights: FP8 checkpoint designed for efficient deployment and serving, including on a single modern GPU.
Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, and Arabic.
Part of the Ministral 3 family: Seamlessly aligned with 3B/8B/14B base, instruct, and reasoning variants for scalable deployments.
Use Cases
Vision + language assistants
Image captioning and explanation (UI screenshots, photos, diagrams)
Multimodal Q&A (e.g., “describe this chart and summarize its implications”)
JSON-structured responses for downstream automation
Text understanding & generation
Classification, tagging, routing, and extraction from long documents
Short-form copywriting, drafting, and rewriting across multiple languages
Edge & low-resource deployments
On-device or near-edge assistants where latency, context length, and cost matter
Local/private workloads that benefit from a small yet capable multimodal model
Inputs and Outputs
Inputs
Text-only prompts
Single-turn or multi-turn chat-style conversations (system, user, assistant roles).
Long-context inputs up to the model’s context limit (e.g., documents, logs, transcripts).
Multimodal prompts
One or more images (e.g., URLs or image tensors) combined with text.
Structured tool schemas
Function / tool definitions for agentic workflows (JSON schemas describing functions and parameters).
Outputs
Generated text
Answers, explanations, step-by-step reasoning, summaries, and creative content.
Multimodal-aware responses
Text grounded in the provided images (descriptions, comparisons, localized details).
Structured tool calls
JSON-like tool call objects for function execution and programmatic integration.
Logits / probabilities (advanced)
For users accessing the raw model via low-level APIs, token-level scores for custom decoding or research.
License
This repo is licensed under the Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0) license, which allows use, sharing, and modification only for non-commercial purposes with proper attribution. All NPU-related models, runtimes, and code in this project are protected under this non-commercial license and cannot be used in any commercial or revenue-generating applications. Commercial licensing or enterprise usage requires a separate agreement. For inquiries, please contact dev@nexa.ai
