unsloth/Phi-4-mini-instruct-GGUF
NewMicrosoft Phi-4-mini distilled for edge reasoning. 3.8B params, 128K context, MIT license. Optimized for agentic tool-calling and multilingual tasks.
reasoningmultilingualtool-calling
Analytics loading...
Similar Models
unsloth/Phi-4-mini-reasoning-GGUF
NewMicrosoft Phi-4-mini distilled for step-by-step reasoning. 3.8B params, 128K context, MIT license. Unsloth bug-fixed GGUF for reliable agentic tool-calling.
reasoningagentictool-calling
Jackrong/Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Distilled-GGUF
NewA 2B dense architecture model fine-tuned with structured step-by-step reasoning trajectories distilled from Claude 4.6 Opus.
reasoningchain-of-thoughtqwen
SmolLM3 3B (Reasoning Specialist)
ggml-org/SmolLM3-3B-GGUF
A 2026-native 3B reasoning model from Hugging Face. Dual-mode `/think` and `/no_think` for agentic workflows with 64K-128K context. Fully open recipe.
How to Use
To get started, install the `transformers` library:
pip install transformersThen, use the following snippet to load the model:
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "ggml-org/SmolLM3-3B-GGUF"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Your inference code here...Available Versions
Model Details
Teacher Model
SmolLM3-Base
Distillation Method
Knowledge Distillation (Logits)
Training Dataset
Flickr30k (Conceptual)
Primary Task
Multimodal Generation
Performance Metrics (Example)
| Metric | Student Model | Teacher Model |
|---|---|---|
| Model Size | 2.1GB | 8.5GB |
| BLEU Score | 28.5 | 30.1 |