HARDWARE FIT CHECK • Mistral Large 2 (123B Instruct) + Apple Mac Studio M2 Ultra (192GB Unified Memory)83.04 GB / 144 GB VRAM

Can I Run Mistral Large 2 (123B Instruct) on Apple Mac Studio M2 Ultra (192GB Unified Memory)?

Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running Mistral Large 2 (123B Instruct) (123B) on Apple Mac Studio M2 Ultra (192GB Unified Memory) (144 GB).

✓ FITS IN VRAM83.04 GB (58%)~7 t/s

Mistral Large 2 (123B Instruct) on Apple Mac Studio M2 Ultra (192GB Unified Memory)

✓ Fits Comfortably in VRAM

✓ FITS IN VRAM

Required VRAM

83.04 GB

58% of hardware capacity (144 GB)

Est. Decode Speed

~7 tok/s

Dense model @ 800 GB/s

Available Headroom

+60.96 GB

Safe for OS display & full context

Memory Allocation & Headroom

83.04 GB allocated of 144 GB capacity

58% utilized

Weights: 73.8 GB

KV: (32K): 5.91 GB

Overhead: 3.33 GB

Free Headroom: +60.96 GB

⚡ Architecture & Throughput Transparency: Single-user decode speed (~7 tok/s) is memory-bandwidth bound at batch size = 1 on Apple Mac Studio M2 Ultra (192GB Unified Memory) (800 GB/s). Prompt prefill / TTFT (~102 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).

OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run mistral-large:123b

Local Hardware Configurations & Pricing

High-bandwidth VRAM specs and current market prices

Multi-GPU Rig

48 GB VRAM

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

Best price-to-VRAM homelab rig for 70B Q4_K_M & Qwen 3.8 27B Q8

936 GB/s700W TDP

$1,550Amazon Prime →

Apple Silicon

112 GB VRAM

Apple Mac Studio M4 Max (128GB Unified Memory)

Running Llama 4 Scout 109B & 70B Q8 locally with 128K+ context

546 GB/s145W TDP

$3,499Amazon Prime →

Apple Silicon Workstation

144 GB VRAM

Apple Mac Studio M2 Ultra (192GB Unified Memory)

Silent 144GB usable unified VRAM running 70B FP16 & 405B Q3

800 GB/s120W TDP

$6,999Amazon Prime →

Cloud Instance Options for Mistral Large 2 (123B Instruct)

On-Demand

Deploy this model on an on-demand cloud GPU without local hardware constraints or power usage:

RunPod Cloud GPUsBest 1-Click Ollama & vLLM

$0.34/hr (RTX 4070 Ti) – $2.39/hr (H100)

Launch 1-Click GPU Pod →

Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090

$0.18/hr (RTX 3060) – $0.55/hr (RTX 4090)

Rent Spot GPU →

Lambda GPU CloudEnterprise 8x H100 Clusters

$1.99/hr (GH200 / H100)

Check H100 Availability →

Quantization Precision Matrix

32K ctx • KV: Q8_0

Quantization	Weights	KV Cache	Total VRAM	Est. Speed	Fit Status
FP1616 bpw	246 GB	5.91 GB	261.27 GB (181%)	0 t/s	OOM
Q8_08.5 bpw	130.38 GB	5.91 GB	141.6 GB (98%)	~4 t/s	FITS
Q6_K6.56 bpw	100.86 GB	5.91 GB	111.05 GB (77%)	~5 t/s	FITS
Q5_K_M5.68 bpw	87.33 GB	5.91 GB	97.05 GB (67%)	~6 t/s	FITS
Q4_K_M4.8 bpw	73.8 GB	5.91 GB	83.04 GB (58%)	~7 t/s	FITS
FP44.25 bpw	65.19 GB	5.91 GB	74.13 GB (51%)	~8 t/s	FITS
IQ3_XS3.3 bpw	50.43 GB	5.91 GB	58.86 GB (41%)	~10 t/s	FITS

Export Full Architecture & Infrastructure Spec

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FAQ & Reference

Frequently Asked Questions: Mistral Large 2 (123B Instruct) on Apple Mac Studio M2 Ultra (192GB Unified Memory)

How much VRAM does Mistral Large 2 (123B Instruct) need on Apple Mac Studio M2 Ultra (192GB Unified Memory)?

At standard 4-bit quantization (Q4_K_M) with 32K context, Mistral Large 2 (123B Instruct) requires 83.04 GB of total VRAM (weights + KV cache + CUDA runtime overhead).

What inference speed will Mistral Large 2 (123B Instruct) achieve on Apple Mac Studio M2 Ultra (192GB Unified Memory)?

Based on Apple Mac Studio M2 Ultra (192GB Unified Memory)'s 800 GB/s memory bandwidth, expected decode speed is approximately 7 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.