Phi-4-mini-reasoningMicrosoft
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Tev1Together AI
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Related Products
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About
Phi-4-mini-reasoning is a 3.8-billion parameter transformer-based language model optimized for mathematical reasoning and step-by-step problem solving in environments with constrained computing or latency. Fine-tuned with synthetic data generated by the DeepSeek-R1 model, it balances efficiency with advanced reasoning ability. Trained on over one million diverse math problems spanning multiple levels of difficulty from middle school to Ph.D. level, Phi-4-mini-reasoning outperforms its base model on long sentence generation across various evaluations and surpasses larger models like OpenThinker-7B, Llama-3.2-3B-instruct, and DeepSeek-R1. It features a 128K-token context window and supports function calling, enabling integration with external tools and APIs. Phi-4-mini-reasoning can be quantized using Microsoft Olive or Apple MLX Framework for deployment on edge devices such as IoT, laptops, and mobile devices.
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About
Tev1 is a fast decision and classification model built by Together AI and fine-tuned from Qwen3.5 4B. It is designed around a simple interface: provide a piece of state, a question, and 2 to 24 labeled options, and the model returns exactly one letter that software can map back to a semantic key. This structure supports production tasks such as routing support tickets, evaluating automated returns, applying policy rules, rating sentiment, categorizing documents, and inserting deterministic decision points into larger agent pipelines. The model has 4.7B parameters, a 32.8K-token context window, and runs with non-thinking generation for fast, predictable classification. It was trained on 37,840 examples spanning intent detection, boolean comprehension, sentiment, policy application, routing, news categories, and research-paper taxonomy. Recommended settings use temperature 0 and a very small output budget so responses remain stable and easy to parse.
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
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On-Premises
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iPhone
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iPad
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Android
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Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers wanting an AI model for educational tools and embedded tutoring
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Audience
Developers and AI engineering teams seeking to route, classify, score, and apply policy decisions through fast, deterministic structured outputs
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Support
Phone Support
Supported
24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
$0.04 per 1M tokens
Free Version
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Free Trial
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Reviews/
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Reviews/
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Training
Documentation
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Webinars
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Live Online
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In Person
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Training
Documentation
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Webinars
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Live Online
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In Person
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Company InformationMicrosoft
Founded: 1975
United States
azure.microsoft.com/en-us/blog/one-year-of-phi-small-language-models-making-big-leaps-in-ai/
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Company InformationTogether AI
Founded: 2022
United States
www.together.ai/models/tev1-4b-experimental
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Categories |
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Integrations
ExecuTorch
Supported
Hugging Face
Supported
Microsoft Azure
Supported
Microsoft Foundry
Supported
Microsoft Foundry Models
Supported
Python
Not Supported
Qwen3.5
Not Supported
TypeScript
Not Supported
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Integrations
ExecuTorch
Not Supported
Hugging Face
Not Supported
Microsoft Azure
Not Supported
Microsoft Foundry
Not Supported
Microsoft Foundry Models
Not Supported
Python
Supported
Qwen3.5
Supported
TypeScript
Supported
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