HARDWARE BENCHMARK & VRAM ENVELOPE โข APPLE SILICON7 GB VRAM โข 68 GB/s
What Models Can Run on Apple MacBook Pro/Air M1 (8GB Unified Memory)?
7 GB VRAM68 GB/s Bandwidth30W TDPMSRP: $999Used / eBay: ~$450Cloud: $0.2/hr on RunPod
Apple MacBook Pro/Air M1 (8GB Unified Memory) provides 7 GB of usable memory with 68 GB/s memory bandwidth at 30W TDP. Compact laptop setup for 1Bโ7B quantized models (Llama 3.2 3B, Qwen 2.5 7B Q4).
โ OOM25.22 GB (360%)0 t/s
Qwen 2.5 Coder 32B Instruct on Apple MacBook Pro/Air M1 (8GB Unified Memory)
โ Out of Memory โ Exceeds VRAM Capacity
โ OOM
Required VRAM
25.22 GB
360% of hardware capacity (7 GB)Est. Decode Speed
0 tok/s
Dense model @ 68 GB/sAvailable Headroom
-18.22 GB
Needs +18.22 GB more VRAMMemory Allocation & Headroom
25.22 GB allocated of 7 GB capacity
360% utilized
Weights: 19.5 GB
KV: (32K): 4.29 GB
Overhead: 1.43 GB
Deficit: -18.22 GB
โก Architecture & Throughput Transparency: Single-user decode speed (~0 tok/s) is memory-bandwidth bound at batch size = 1 on Apple MacBook Pro/Air M1 (8GB Unified Memory) (68 GB/s). Prompt prefill / TTFT (~0 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).
โ ๏ธ Out of VRAM? Don't downgrade model quality.
Out of VRAMSpin up an on-demand cloud GPU instance in 60 seconds with pre-installed Ollama and vLLM. (Qwen 2.5 Coder 32B Instruct @ 25.22 GB VRAM)
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) โ $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) โ $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx โข KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 65 GB | 4.29 GB | 72.32 GB (999%) | 0 t/s | OOM |
| Q8_08.5 bpw | 34.45 GB | 4.29 GB | 40.7 GB (581%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 26.65 GB | 4.29 GB | 32.62 GB (466%) | 0 t/s | OOM |
| Q5_K_M5.68 bpw | 23.07 GB | 4.29 GB | 28.92 GB (413%) | 0 t/s | OOM |
| Q4_K_M4.8 bpw | 19.5 GB | 4.29 GB | 25.22 GB (360%) | 0 t/s | OOM |
| FP44.25 bpw | 17.23 GB | 4.29 GB | 22.87 GB (327%) | 0 t/s | OOM |
| IQ3_XS3.3 bpw | 13.32 GB | 4.29 GB | 18.83 GB (269%) | 0 t/s | OOM |
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All Open-Weights Models Tested on Apple MacBook Pro/Air M1 (8GB Unified Memory) (Q4_K_M @ 32K Context)
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Model | Architecture | Total VRAM Needed | Headroom | Est. Decode Speed | Compatibility | Detailed Config |
|---|---|---|---|---|---|---|
| Qwen 2.5 Coder 32B Instruct Alibaba Cloud | 32.5B Dense | 25.22 GB(360%) | -18.22 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| DeepSeek-R1 (671B MoE) DeepSeek | 671B MoE | 482.94 GB(999%) | -475.94 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| DeepSeek-V3 (671B MoE) DeepSeek | 671B MoE | 482.94 GB(999%) | -475.94 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Meta Llama 3.3 70B Instruct Meta AI | 70.6B Dense | 49.96 GB(714%) | -42.96 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| DeepSeek-R1 Distill Qwen 32B DeepSeek | 32.8B Dense | 25.41 GB(363%) | -18.41 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| DeepSeek-R1 Distill Qwen 14B DeepSeek | 14.8B Dense | 13.16 GB(188%) | -6.16 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Qwen 2.5 72B Instruct Alibaba Cloud | 72.7B Dense | 51.27 GB(732%) | -44.27 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Meta Llama 3.1 8B Instruct Meta AI | 8B Dense | 7.87 GB(112%) | -0.87 GB | ~2 tok/s | โก PARTIAL | Configure CLI โ |
| Microsoft Phi-4 14B Microsoft | 14.7B Dense | 13.24 GB(189%) | -6.24 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| DeepSeek Coder V2 236B MoE DeepSeek | 236B MoE | 151.34 GB(999%) | -144.34 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Mistral Large 2 (123B Instruct) Mistral AI | 123B Dense | 83.04 GB(999%) | -76.04 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Meta Llama 3.1 405B Instruct Meta AI | 405B Dense | 260.72 GB(999%) | -253.72 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Google Gemma 2 27B Instruct Google | 27.2B Dense | 23.81 GB(340%) | -16.81 GB | 0 (OOM) | โ OOM | Configure CLI โ |
| Google Gemma 2 9B Instruct Google | 9.2B Dense | 12.1 GB(173%) | -5.1 GB | 0 (OOM) | โ OOM | Configure CLI โ |