Leaderboard / Microsoft (Phi)
Phi-4-mini
Microsoft (Phi) · Phi-4 · released 2025-02-26 · data checked 2026-11-01 Needs verification
Phi-4-mini is a 3.8B-parameter dense model from Microsoft (Phi) (United States), released 2025-02-26 under the MIT license. It doesn't have enough reported benchmarks for an index score yet. It needs about 4 GB of memory at 4-bit with an 8K-token context.
Small LM Index
—
Needs 2 core benchmarks (has 1)
Parameters
3.8B
Dense
Price per 1M tokens
—
No hosted API on OpenRouter; self-host
Context window
128K
tokens
Benchmarks
Each bar shows this model's score. The tick marks the best tiny model on that benchmark. Sources: 1 reported by Microsoft (Phi). How we label sources.
Specifications
- Lab
- Microsoft (Phi) (US · United States)
- Architecture
- Dense transformer
- Total parameters
- 3.8B
- Active parameters
- All (dense)
- Size class
- Tiny
- Context window
- 128K tokens
- Input modalities
- text
- Reasoning
- Instruct (no thinking)
- License
- MIT
- Openness
- Open weights
- Memory to run
- ~4 GB at 4-bit, 8K context (more sizes)
- Hugging Face
- 343.6K downloads (30 days) · 878 likes
Compare with
- Phi-4-mini vs Nemotron Labs Dory 1.0 4B (4B, index 60.0)
- Phi-4-mini vs Qwen3.5 4B (4B, index 57.8)
- Phi-4-mini vs Qwen3 4B Thinking 2507 (4B, index 55.7)
Sources
Something wrong here? Report it.
Run it locally
Uses unsloth/Phi-4-mini-instruct-GGUF (Q4_K_M). Swap the tag for another size: BF16, Q2_K, Q2_K_L, Q3_K_M, Q4_K_M, Q5_K_M, Q6_K, Q8_0.
Ollama
ollama run hf.co/unsloth/Phi-4-mini-instruct-GGUF:Q4_K_Mllama.cpp
llama-server -hf unsloth/Phi-4-mini-instruct-GGUF:Q4_K_MThen open http://localhost:8080 for a chat window.
MLX (Mac)
pip install -U mlx-lm
mlx_lm.chat --model mlx-community/Phi-4-mini-instruct-4bitvLLM (GPU server)
vllm serve microsoft/Phi-4-mini-instructFull-precision weights, for a server GPU.
Memory needed: weights, context cache and runtime buffers.
| Quantization | 4K context | 32K context | 128K context |
|---|---|---|---|
| 16-bit F16 | 8.7 GB | 12 GB | 25 GB |
| 8-bit Q8_0 | 5.2 GB | 8.9 GB | 21 GB |
| 4-bit Q4_K_M | 3.4 GB | 7.2 GB | 20 GB |