Will It Run AI

Can Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 run on Mac Studio M3 Ultra 96GB?

YES — Runs Great

C48Usable
Estimated from fit model

Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 needs ~28.7 GB VRAM. Mac Studio M3 Ultra 96GB has 69.1 GB. With Q4_K_M quantization, expect ~38 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: 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) — 28.7 GB, 38.0 tok/s, Runs well
28.7 GB required69.1 GB available
42% VRAM used

Fit status

Runs well

Decode

38.0 tok/s

TTFT

5089 ms

Safe context

246K

Memory

28.7 GB / 69.1 GB

Memory breakdown

Weights14.6 GB
KV Cache2.8 GB
Runtime0.9 GB
Headroom10.4 GB

See how fast it feels

See how fast it feelsDolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 on Mac Studio M3 Ultra 96GB
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: 38.0 tok/s decode · 5.1s TTFT (warm) · 95 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
ChatCRuns well38.0 tok/s2776 ms246K
CodingCRuns well38.0 tok/s5089 ms246K
Agentic CodingCRuns well38.0 tok/s7403 ms246K
ReasoningCRuns well38.0 tok/s6015 ms246K
RAGCRuns well38.0 tok/s9253 ms246K

Quantization options

How Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 (24B params) fits at each quantization level on Mac Studio M3 Ultra 96GB (69.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowC41
Q3_K_S
3
11.8 GB
LowC41
NVFP4
4
13.4 GB
MediumC41
Q4_K_M
4
14.6 GB
MediumC42
Q5_K_M
5
17.3 GB
HighC42
Q6_K
6
19.7 GB
HighC43
Q8_0
8
25.7 GB
Very HighC44
F16Best for your GPU
16
49.2 GB
MaximumC48

Get started

Copy-paste commands to run Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 on your machine.

Run

lms load hf-mradermacher--dolphin-mistral-glm-4-7-flash-24b-venice-edition-thinking-uncensored-i1-gguf && lms server start

升级选项

能流畅运行 Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 的硬件

NVIDIARTX PRO 6000 Blackwell Workstation Edition 96GB经济之选
1792 GB/s (+973)
C
Raises estimated decode speed by about 171%.102.8 tok/s 解码

Raises estimated decode speed by about 171%.

Adds memory headroom for longer context windows and future model growth.

~$9,999 MSRP

NVIDIARTX PRO 6000 Blackwell Server Edition 96GB最佳性价比
1597 GB/s (+778)
C
Raises estimated decode speed by about 141%.91.6 tok/s 解码

Raises estimated decode speed by about 141%.

Adds memory headroom for longer context windows and future model growth.

~$9,999 MSRP

Frequently asked questions

Can Mac Studio M3 Ultra 96GB run Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1?

Yes, Mac Studio M3 Ultra 96GB can run Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 with a C grade (Runs well). Expected decode speed: 38.0 tok/s.

How much VRAM does Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 need?

Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 (24B parameters) requires approximately 28.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1?

The recommended quantization for Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 is Q4_K_M, which balances quality and memory efficiency.

What speed will Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 run at on Mac Studio M3 Ultra 96GB?

On Mac Studio M3 Ultra 96GB, Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 achieves approximately 38.0 tokens per second decode speed with a time-to-first-token of 5089ms using Q4_K_M quantization.

Can Mac Studio M3 Ultra 96GB run Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 for coding?

For coding workloads, Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 on Mac Studio M3 Ultra 96GB receives a C grade with 38.0 tok/s and 246K context.

What context window can Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 use on Mac Studio M3 Ultra 96GB?

On Mac Studio M3 Ultra 96GB, Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1 can safely use up to 246K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

Is unified memory on Mac Studio M3 Ultra 96GB as fast as VRAM for Dolphin Mistral GLM 4.7 Flash 24B Venice Edition Thinking Uncensored i1?

Not always. Mac Studio M3 Ultra 96GB 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.

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