Phi 3 Medium 4k Instruct — Hardware Requirements & GPU Compatibility
ChatCode
11.3K downloads
225 likesSpecifications
- Publisher
- Microsoft
- Family
- Phi 3
- Parameters
- 14.0B
- Architecture
- Phi3ForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 32,064
- Release Date
- 2025-12-10
- License
- MIT
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HuggingFace
How Much VRAM Does Phi 3 Medium 4k Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 28.6 GB | 29.1 GB | 27.92 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Phi 3 Medium 4k Instruct?
BF16 · 28.6 GBPhi 3 Medium 4k Instruct (BF16) requires 28.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 38+ GB is recommended. Using the full 4K context window can add up to 0.4 GB, bringing total usage to 29.1 GB. 1 GPU can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Decent
— Enough VRAM, may be tightWhich Devices Can Run Phi 3 Medium 4k Instruct?
BF16 · 28.6 GB15 devices with unified memory can run Phi 3 Medium 4k Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Phi 3 Medium 4k Instruct need?
Phi 3 Medium 4k Instruct requires 28.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 14.0B × 16 bits ÷ 8 = 27.9 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 1.2 GB (at full 4K context)
VRAM usage by quantization
BF1628.6 GBBF16 + full context29.1 GB- Can I run Phi 3 Medium 4k Instruct on a Mac?
Phi 3 Medium 4k Instruct requires at least 28.6 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Phi 3 Medium 4k Instruct locally?
Yes — Phi 3 Medium 4k Instruct can run locally on consumer hardware. At BF16 quantization it needs 28.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Phi 3 Medium 4k Instruct?
At BF16, Phi 3 Medium 4k Instruct can reach ~102 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 28.6 × 0.55 = ~102 tok/s
Estimated speed at BF16 (28.6 GB)
AMD Instinct MI300X~102 tok/sNVIDIA H100 SXM~76 tok/sAMD Instinct MI250X~63 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Phi 3 Medium 4k Instruct?
At BF16, the download is about 27.92 GB.
- Which GPUs can run Phi 3 Medium 4k Instruct?
1 consumer GPU can run Phi 3 Medium 4k Instruct at BF16 (28.6 GB). Top options include NVIDIA GeForce RTX 5090.
- Which devices can run Phi 3 Medium 4k Instruct?
15 devices with unified memory can run Phi 3 Medium 4k Instruct at BF16 (28.6 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.