Will It Run AI

Can Mixtral 8x7B run on Mac Studio M1 Ultra 64GB?

YES — Tight Fit

B66Good
Estimated from fit model

Mixtral 8x7B needs ~38.4 GB VRAM. Mac Studio M1 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~29 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: HighStack: StandardBottleneck: Balanced
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Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 38.4 GB, 31.6 tok/s, Tight fit
38.4 GB required46.1 GB available
83% VRAM used

Fit status

Tight fit

Decode

31.6 tok/s

TTFT

6117 ms

Safe context

33K

Memory

38.4 GB / 46.1 GB

Memory breakdown

Weights28.7 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom6.9 GB

See how fast it feels

See how fast it feelsMixtral 8x7B on Mac Studio M1 Ultra 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 31.6 tok/s decode · 6.1s TTFT (warm) · 79 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Shared-memory contention still exists

The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well31.6 tok/s3337 ms33K
CodingBTight fit29.4 tok/s6576 ms33K
Agentic CodingBTight fit31.6 tok/s8897 ms33K
ReasoningBTight fit31.6 tok/s7229 ms33K
RAGBTight fit31.6 tok/s11122 ms33K

Quantization options

How Mixtral 8x7B (47B params) fits at each quantization level on Mac Studio M1 Ultra 64GB (46.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
18.3 GB
LowB62
Q3_K_S
3
23.0 GB
LowB64
NVFP4
4
26.3 GB
MediumB64
Q4_K_M
4
28.7 GB
MediumB63
Q5_K_MBest for your GPU
5
33.8 GB
HighB63
Q6_K
6
38.5 GB
HighF0
Q8_0
8
50.3 GB
Very HighF0
F16
16
96.4 GB
MaximumF0

Get started

Copy-paste commands to run Mixtral 8x7B on your machine.

Run

ollama run mixtral

Opciones de mejora

Hardware que ejecuta bien Mixtral 8x7B

MacBook Pro M4 Max 96GBOpción económica
96 GB Unified (+32)
B
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.24.7 tok/s decodificación

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$2,499 MSRP

Mac Studio M3 Ultra 96GBMejor relación calidad-precio
96 GB Unified (+32)819 GB/s (+19)
B
Sube la velocidad estimada de decodificación alrededor de un 27%.40.1 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 27%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$3,999 MSRP

Frequently asked questions

Can Mac Studio M1 Ultra 64GB run Mixtral 8x7B?

Yes, Mac Studio M1 Ultra 64GB can run Mixtral 8x7B with a B grade (Tight fit). Expected decode speed: 29.4 tok/s.

How much VRAM does Mixtral 8x7B need?

Mixtral 8x7B (47B parameters) requires approximately 38.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Mixtral 8x7B?

The recommended quantization for Mixtral 8x7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Mixtral 8x7B run at on Mac Studio M1 Ultra 64GB?

On Mac Studio M1 Ultra 64GB, Mixtral 8x7B achieves approximately 29.4 tokens per second decode speed with a time-to-first-token of 6576ms using Q4_K_M quantization.

Can Mac Studio M1 Ultra 64GB run Mixtral 8x7B for coding?

For coding workloads, Mixtral 8x7B on Mac Studio M1 Ultra 64GB receives a B grade with 29.4 tok/s and 33K context.

What context window can Mixtral 8x7B use on Mac Studio M1 Ultra 64GB?

On Mac Studio M1 Ultra 64GB, Mixtral 8x7B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

Is unified memory on Mac Studio M1 Ultra 64GB as fast as VRAM for Mixtral 8x7B?

Not always. Mac Studio M1 Ultra 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.

See all results for Mac Studio M1 Ultra 64GBSee all hardware for Mixtral 8x7B
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