HARDWARE FIT CHECK • DeepSeek-R1 Distill Qwen 14B + Apple MacBook Pro M4 Pro (24GB Unified Memory)13.16 GB / 20 GB VRAM

Can I Run DeepSeek-R1 Distill Qwen 14B on Apple MacBook Pro M4 Pro (24GB Unified Memory)?

Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running DeepSeek-R1 Distill Qwen 14B (14.8B) on Apple MacBook Pro M4 Pro (24GB Unified Memory) (20 GB).

✓ FITS IN VRAM13.16 GB (66%)~18 t/s

Target Hardware & Model

interactive
Fast reasoning assistant for 12GB–16GB consumer GPUs (RTX 4070 / 4080)
DeepSeek-R1 Distill Qwen 14B on Apple MacBook Pro M4 Pro (24GB Unified Memory)

✓ Fits Comfortably in VRAM

✓ FITS IN VRAM
Required VRAM
13.16 GB
66% of hardware capacity (20 GB)
Est. Decode Speed
~18 tok/s
Dense model @ 273 GB/s
Available Headroom
+6.84 GB
Safe for OS display & full context
Memory Allocation & Headroom
13.16 GB allocated of 20 GB capacity
66% utilized
Weights: 8.88 GB
KV: (32K): 3.22 GB
Overhead: 1.06 GB
Free Headroom: +6.84 GB
Architecture & Throughput Transparency: Single-user decode speed (~18 tok/s) is memory-bandwidth bound at batch size = 1 on Apple MacBook Pro M4 Pro (24GB Unified Memory) (273 GB/s). Prompt prefill / TTFT (~261 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).

Local Hardware Configurations & Pricing

High-bandwidth VRAM specs and current market prices
Consumer GPU
32 GB VRAM

NVIDIA GeForce RTX 5090 (32GB GDDR7)

Maximum tokens/sec on 27B–35B models & Blackwell FP4 quantization

1792 GB/s575W TDP
Consumer GPU
24 GB VRAM

NVIDIA GeForce RTX 4090 (24GB GDDR6X)

The 24GB CUDA enthusiast standard for 14B–32B Q4_K_M models

1008 GB/s450W TDP
Multi-GPU Rig
48 GB VRAM

2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM)

Best price-to-VRAM homelab rig for Llama 3.3 70B Q4_K_M & Qwen 2.5 Coder 32B Q8_0

1648 GB/s700W TDP
Apple Silicon
20 GB VRAM

Apple MacBook Pro M4 Pro (24GB Unified Memory)

Portable 273 GB/s laptop running 14B–27B Q4_K_M models (Qwen 3.8 27B, Gemma 4 26B MoE)

273 GB/s45W TDP

Quantization Precision Matrix

32K ctx • KV: Q8_0
QuantizationWeightsKV CacheTotal VRAMEst. SpeedFit Status
FP1616 bpw29.6 GB3.22 GB34.61 GB (173%)0 t/sOOM
Q8_08.5 bpw15.69 GB3.22 GB20.21 GB (101%)~2 t/sPARTIAL
Q6_K6.56 bpw12.14 GB3.22 GB16.53 GB (83%)~13 t/sFITS
Q5_K_M5.68 bpw10.51 GB3.22 GB14.85 GB (74%)~15 t/sFITS
Q4_K_M4.8 bpw8.88 GB3.22 GB13.16 GB (66%)~18 t/sFITS
FP44.25 bpw7.84 GB3.22 GB12.08 GB (60%)~20 t/sFITS
IQ3_XS3.3 bpw6.07 GB3.22 GB10.25 GB (51%)~25 t/sFITS

Export Full Architecture & Infrastructure Spec

Download an instant Markdown architecture spec with exact memory math, hardware benchmarks, and runtime CLI flags.

FAQ & Reference

Frequently Asked Questions: DeepSeek-R1 Distill Qwen 14B on Apple MacBook Pro M4 Pro (24GB Unified Memory)

How much VRAM does DeepSeek-R1 Distill Qwen 14B need on Apple MacBook Pro M4 Pro (24GB Unified Memory)?

At standard 4-bit quantization (Q4_K_M) with 32K context, DeepSeek-R1 Distill Qwen 14B requires 13.16 GB of total VRAM (weights + KV cache + CUDA runtime overhead).

What inference speed will DeepSeek-R1 Distill Qwen 14B achieve on Apple MacBook Pro M4 Pro (24GB Unified Memory)?

Based on Apple MacBook Pro M4 Pro (24GB Unified Memory)'s 273 GB/s memory bandwidth, expected decode speed is approximately 18 tokens per second.

Can I expand context beyond 32K tokens?

Each additional 32K tokens of context requires additional KV cache memory. For longer context windows, consider 8-bit or 4-bit KV cache quantization.