Ministral 3 8B Instruct 2512 GGUF
mistralai/ministral-8b-2512Ministral 3 8B Instruct 2512 GGUF (mistralai/ministral-8b-2512) is an AI model from Mistral AI with a 262,144-token context window and 262,144 max output tokens, priced at $0.15/1M input and $0.15/1M output tokens. Available via the haimaker.ai OpenAI-compatible API.
Overview
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
Model Card
Ministral 3 8B Instruct 2512 GGUF
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
This model includes different quantization levels of the instruct post-trained version in GGUF, fine-tuned for instruction tasks, making it ideal for chat and instruction based use cases.
The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 12GB of VRAM in FP8, and less if further quantized.
Learn more in our blog post and paper.
Key Features
Ministral 3 8B consists of two main architectural components:- 8.4B Language Model
- 0.4B Vision Encoder
- Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text.
- Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic.
- System Prompt: Maintains strong adherence and support for system prompts.
- Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting.
- Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere.
- Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes.
- Large Context Window: Supports a 256k context window.
Recommended Settings
We recommend deploying with the following best practices:
- System Prompt: Define a clear environment and use case, including guidance on how to effectively leverage tools in agentic systems.
- Sampling Parameters: Use a temperature below 0.1 for daily-driver and production environments ; Higher temperatures may be explored for creative use cases - developers are encouraged to experiment with alternative settings.
- Tools: Keep the set of tools well-defined and limit their number to the minimum required for the use case - Avoiding overloading the model with an excessive number of tools.
- Vision: When deploying with vision capabilities, we recommend maintaining an aspect ratio close to 1:1 (width-to-height) for images. Avoiding the use of overly thin or wide images - crop them as needed to ensure optimal performance.
License
This model is licensed under the Apache 2.0 License.
You must not use this model in a manner that infringes, misappropriates, or otherwise violates any third party’s rights, including intellectual property rights.Features & Capabilities
| Mode | chat |
| Context Window | 262,144 tokens |
| Max Output | 262,144 tokens |
| Function Calling | Supported |
| Vision | Supported |
| Reasoning | Not supported |
| Web Search | Not supported |
| Url Context | Not supported |
Technical Details
| Base Model | mistralai/Ministral-3-8B-Instruct-2512 |
| Languages | en, fr, es, de, it, pt, nl, zh, ja, ko, ar |
| Library | vllm |
API Usage
from openai import OpenAI
client = OpenAI(
base_url="https://api.haimaker.ai/v1",
api_key="YOUR_API_KEY",
)
response = client.chat.completions.create(
model="mistralai/ministral-8b-2512",
messages=[
{"role": "user", "content": "Hello, how are you?"}
],
)
print(response.choices[0].message.content)Frequently Asked Questions
What is the context window of Ministral 3 8B Instruct 2512 GGUF?
Ministral 3 8B Instruct 2512 GGUF (mistralai/ministral-8b-2512) has a 262,144-token context window and supports up to 262,144 output tokens per request.
How much does Ministral 3 8B Instruct 2512 GGUF cost?
Ministral 3 8B Instruct 2512 GGUF is priced at $0.15 per 1M input tokens and $0.15 per 1M output tokens when accessed via the haimaker.ai OpenAI-compatible API.
What features does Ministral 3 8B Instruct 2512 GGUF support?
Ministral 3 8B Instruct 2512 GGUF supports function calling, vision.
How do I use Ministral 3 8B Instruct 2512 GGUF via API?
Send requests to https://api.haimaker.ai/v1/chat/completions with model "mistralai/ministral-8b-2512" using any OpenAI-compatible SDK. Authentication uses a Bearer API key from https://app.haimaker.ai.
Use Ministral 3 8B Instruct 2512 GGUF with the haimaker API
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