Can Solar Open 69B REAP i1 run on MacBook Pro M3 Max 128GB?

YES — Runs Great

C48Usable

Estimated from fit model

Solar Open 69B REAP i1 needs ~64.9 GB VRAM. MacBook Pro M3 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~6 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Memory bandwidth

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) — 64.9 GB, 5.7 tok/s, Runs well

64.9 GB required92.2 GB available

70% VRAM used

Fit status

Runs well

Decode

5.7 tok/s

TTFT

33953 ms

Safe context

70K

Memory

64.9 GB / 92.2 GB

Memory breakdown

Weights42.1 GB

KV Cache8.1 GB

Runtime0.9 GB

Headroom13.8 GB

See how fast it feels

See how fast it feelsSolar Open 69B REAP i1 on MacBook Pro M3 Max 128GB
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: 5.7 tok/s decode · 34.0s TTFT (warm) · 14 tok/s prefill

What limits this setup

The model fits in shared memory, but shared-memory bandwidth is now the real limiter.

Fit does not mean dedicated-VRAM speed

Unified or shared memory can make a model technically fit, but sustained tokens per second may still trail a discrete high-bandwidth GPU with less total memory.

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

Prioritize bandwidth, not only capacity

If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Runs well	5.7 tok/s	18520 ms	70K
Coding	C	Runs well	5.7 tok/s	33953 ms	70K
Agentic Coding	C	Runs well	5.7 tok/s	49386 ms	70K
Reasoning	C	Runs well	5.7 tok/s	40126 ms	70K
RAG	C	Runs well	5.7 tok/s	61732 ms	70K

Inference speed

Solar Open 69B REAP i1 inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Solar Open 69B REAP i1 at Q4_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is 2× RX 7900 XTX 24GB at ~15 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / Mac	Memory	Quant	Speed (tok/s)	Fits?
2× RX 7900 XTX 24GB	48 GB	Q4_K_M	15.2	Heavy offload
MacBook Pro M4 Max 128GB	128 GB	Q4_K_M	14.3	Fits
Mac Studio M3 Ultra 256GB	256 GB	Q4_K_M	13.2	Fits
Mac Studio M2 Ultra 128GB	128 GB	Q4_K_M	11.0	Fits
Mac Studio M1 Ultra 128GB	128 GB	Q4_K_M	10.5	Fits
MacBook Pro M4 Max 64GB	64 GB	Q4_K_M	10.2	Too big
2× RTX 4090 24GB	48 GB	Q4_K_M	8.0	Heavy offload
RTX 5090 32GB	32 GB	Q4_K_M	7.3	Too big
2× RTX 3090 24GB	48 GB	Q4_K_M	7.3	Heavy offload
4× RTX 3060 12GB	48 GB	Q4_K_M	6.5	Heavy offload
MacBook Pro M4 Pro 48GB	48 GB	Q4_K_M	4.8	Too big
MacBook Pro M3 Max 64GB	64 GB	Q4_K_M	4.1	Too big
MacBook Pro M1 Max 64GB	64 GB	Q4_K_M	3.8	Too big
RTX 4090 24GB	24 GB	Q4_K_M	2.7	Too big
RX 7900 XTX 24GB	24 GB	Q4_K_M	2.5	Too big
RTX 3090 24GB	24 GB	Q4_K_M	2.3	Too big
RTX 4080 Super 16GB	16 GB	Q4_K_M	2.2	Too big
RTX 4070 12GB	12 GB	Q4_K_M	2.0	Too big
RTX 3060 12GB	12 GB	Q4_K_M	2.0	Too big
RTX 4060 8GB	8 GB	Q4_K_M	2.0	Too big

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Solar Open 69B REAP i1 (69B params) fits at each quantization level on MacBook Pro M3 Max 128GB (92.2 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	26.9 GB	Low	C42
Q3_K_S	3	33.8 GB	Low	C44
NVFP4	4	38.6 GB	Medium	C45
Q4_K_M	4	42.1 GB	Medium	C46
Q5_K_M	5	49.7 GB	High	C47
Q6_K	6	56.6 GB	High	C48
Q8_0Best for your GPU	8	73.8 GB	Very High	C48
F16	16	141.5 GB	Maximum	F0

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

Opções de upgrade

Hardware que roda bem Solar Open 69B REAP i1

RTX PRO 6000 Blackwell Workstation Edition 96GBOpção econômica

1792 GB/s (+1392)

Raises estimated decode speed by about 528%.35.8 tok/s decodificação

Raises estimated decode speed by about 528%.

Moves the workload away from shared memory into dedicated accelerator memory.

~$9,999 MSRP

RTX PRO 6000 Blackwell Server Edition 96GBMelhor custo-benefício

1597 GB/s (+1197)

Raises estimated decode speed by about 460%.31.9 tok/s decodificação

Raises estimated decode speed by about 460%.

Moves the workload away from shared memory into dedicated accelerator memory.

~$9,999 MSRP

Frequently asked questions

Can MacBook Pro M3 Max 128GB run Solar Open 69B REAP i1?

Yes, MacBook Pro M3 Max 128GB can run Solar Open 69B REAP i1 with a C grade (Runs well). Expected decode speed: 5.7 tok/s.

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

Solar Open 69B REAP i1 (69B parameters) requires approximately 64.9 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 MacBook Pro M3 Max 128GB?

On MacBook Pro M3 Max 128GB, Solar Open 69B REAP i1 achieves approximately 5.7 tokens per second decode speed with a time-to-first-token of 33953ms using Q4_K_M quantization.

Can MacBook Pro M3 Max 128GB run Solar Open 69B REAP i1 for coding?

For coding workloads, Solar Open 69B REAP i1 on MacBook Pro M3 Max 128GB receives a C grade with 5.7 tok/s and 70K context.

What context window can Solar Open 69B REAP i1 use on MacBook Pro M3 Max 128GB?

On MacBook Pro M3 Max 128GB, Solar Open 69B REAP i1 can safely use up to 70K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

What should I upgrade first if Solar Open 69B REAP i1 feels slow on MacBook Pro M3 Max 128GB?

Prioritize bandwidth, not only capacity. If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.

Is unified memory on MacBook Pro M3 Max 128GB as fast as VRAM for Solar Open 69B REAP i1?

Not always. MacBook Pro M3 Max 128GB 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 MacBook Pro M3 Max 128GB See all hardware for Solar Open 69B REAP i1

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