Will It Run AI

Can Solar Open 69B REAP i1 run on Mac Studio M3 Ultra 256GB?

YES — Runs Great

C45Usable
Estimated from fit model

Solar Open 69B REAP i1 needs ~78.7 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~13 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) — 78.7 GB, 13.2 tok/s, Runs well
78.7 GB required184.3 GB available
43% VRAM used

Fit status

Runs well

Decode

13.2 tok/s

TTFT

14632 ms

Safe context

225K

Memory

78.7 GB / 184.3 GB

Memory breakdown

Weights42.1 GB
KV Cache8.1 GB
Runtime0.9 GB
Headroom27.6 GB

See how fast it feels

See how fast it feelsSolar Open 69B REAP i1 on Mac Studio M3 Ultra 256GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API. When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed. Key benefits of running locally: - Full privacy: your prompts never leave your machine - No per-token cost or rate limits - Works offline once the model is downloaded - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb: Model size Q4 (4-bit) Q8 (8-bit) FP16 7B params ~4.3 GB ~7.5 GB ~14 GB 13B params ~7.9 GB ~13.9 GB ~26 GB 70B params ~42.7 GB ~74.9 GB ~140 GB Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 13.2 tok/s decode · 14.6s TTFT (warm) · 33 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 well13.2 tok/s7981 ms225K
CodingCRuns well13.2 tok/s14632 ms225K
Agentic CodingCRuns well13.2 tok/s21282 ms225K
ReasoningCRuns well13.2 tok/s17292 ms225K
RAGCRuns well13.2 tok/s26603 ms225K

Quantization options

How Solar Open 69B REAP i1 (69B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
26.9 GB
LowD38
Q3_K_S
3
33.8 GB
LowD39
NVFP4
4
38.6 GB
MediumD40
Q4_K_M
4
42.1 GB
MediumC40
Q5_K_M
5
49.7 GB
HighC41
Q6_K
6
56.6 GB
HighC42
Q8_0
8
73.8 GB
Very HighC44
F16Best for your GPU
16
141.5 GB
MaximumC48

Get started

Copy-paste commands to run Solar Open 69B REAP i1 on your machine.

Run

lms load hf-mradermacher--solar-open-69b-reap-i1-gguf && lms server start

Upgrade-Optionen

Hardware, die Solar Open 69B REAP i1 gut ausführt

AMD Instinct MI350X 288GBGünstige Wahl
288 GB VRAM (+32)8000 GB/s (+7181)
C
Raises estimated decode speed by about 952%.138.8 tok/s Dekodierung

Raises estimated decode speed by about 952%.

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

ca. $8,000 MSRP

AMD Instinct MI300X 192GBBestes Preis-Leistungs-Verhältnis
5300 GB/s (+4481)
C
Raises estimated decode speed by about 644%.98.2 tok/s Dekodierung

Raises estimated decode speed by about 644%.

ca. $15,000 MSRP

Frequently asked questions

Can Mac Studio M3 Ultra 256GB run Solar Open 69B REAP i1?

Yes, Mac Studio M3 Ultra 256GB can run Solar Open 69B REAP i1 with a C grade (Runs well). Expected decode speed: 13.2 tok/s.

How much VRAM does Solar Open 69B REAP i1 need?

Solar Open 69B REAP i1 (69B parameters) requires approximately 78.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Solar Open 69B REAP i1?

The recommended quantization for Solar Open 69B REAP i1 is Q4_K_M, which balances quality and memory efficiency.

What speed will Solar Open 69B REAP i1 run at on Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, Solar Open 69B REAP i1 achieves approximately 13.2 tokens per second decode speed with a time-to-first-token of 14632ms using Q4_K_M quantization.

Can Mac Studio M3 Ultra 256GB run Solar Open 69B REAP i1 for coding?

For coding workloads, Solar Open 69B REAP i1 on Mac Studio M3 Ultra 256GB receives a C grade with 13.2 tok/s and 225K context.

What context window can Solar Open 69B REAP i1 use on Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, Solar Open 69B REAP i1 can safely use up to 225K 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 256GB as fast as VRAM for Solar Open 69B REAP i1?

Not always. Mac Studio M3 Ultra 256GB 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 M3 Ultra 256GBSee all hardware for Solar Open 69B REAP i1
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