OSAIM
Open Source AI Models

Comparison

Llama 3.2 3B vs Phi-3 Mini 4K Instruct

Side-by-side specs, benchmarks and hosted-inference pricing.

Side A
Llama 3.2 3B
Meta · Llama

Pocket-sized Llama 3 variant for edge deployment. Surprising chat quality after instruction tuning makes it competitive with much larger models from a previous generation. At Q4 it fits in ~2 GB of VRAM and runs on consumer GPUs and recent Apple Silicon. A strong default for on-device chat, summarisation, and structured extraction tasks where the workload doesn't need frontier reasoning quality.

Side B
Phi-3 Mini 4K Instruct
Microsoft · Phi

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.

Specs

Parameters3B3.8B
Context length128K4K
Modalitytexttext
Released2024-09-252024-04-23
LicenseLlama 3 Community LicenseMIT
Commercial useYesYes
VRAM fp166 GB7.6 GB
VRAM Q41.8 GB2.3 GB

Benchmarks

HumanEval51.559.1
MATH48.028.0
MMLU63.468.8

Cheapest hosted pricing

Llama 3.2 3B
groq: $0.06 in / $0.06 out per 1M tokens
Phi-3 Mini 4K Instruct
deepinfra: $0.08 in / $0.08 out per 1M tokens
Highlighted cells indicate the better value for that row (higher score, larger context, lower VRAM).