Phi-3 Mini 4K Instruct
Microsoft's flagship small-model demonstration: GPT-3.5-class on academic benchmarks at <4B parameters. The 4K context-window variant is the lightest; a 128K variant ships separately.
MIT licensed, well-suited to on-device assistants and structured-extraction workloads where compactness matters more than absolute quality.
- Parameters
- 3.8B
- Context length
- 4K
- Modality
- text
- Released
- 2024-04-23
Memory & hardware
- VRAM (fp16)
- 7.6 GB
- VRAM (Q4)
- 2.3 GB
- Recommended
- RTX 3060 12GB or M1 Pro
- Quantizations
- fp16, q8_0, q4_k_m, gguf
Benchmarks
Hosted inference pricing
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| deepinfraCheapest | $0.08 | $0.08 |
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run phi3
vllm serve microsoft/Phi-3-mini-4k-instruct
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
model = AutoModelForCausalLM.from_pretrained(
"microsoft/Phi-3-mini-4k-instruct", device_map="auto", torch_dtype="auto"
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