Will It Run AI

Can Solar Open 69B REAP i1 run on RTX PRO 6000 Blackwell Server Edition 96GB?

YES — Runs Great

C52Usable
Estimated from fit model

Solar Open 69B REAP i1 needs ~61.0 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~32 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) — 61.0 GB, 31.9 tok/s, Runs well
61.0 GB required96.0 GB available
64% VRAM used

Fit status

Runs well

Decode

31.9 tok/s

TTFT

6074 ms

Safe context

85K

Memory

61.0 GB / 96.0 GB

Memory breakdown

Weights42.1 GB
KV Cache8.1 GB
Runtime1.2 GB
Headroom9.6 GB

See how fast it feels

See how fast it feelsSolar Open 69B REAP i1 on RTX PRO 6000 Blackwell Server Edition 96GB
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: 31.9 tok/s decode · 6.1s TTFT (warm) · 80 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well31.9 tok/s3313 ms85K
CodingCRuns well31.9 tok/s6074 ms85K
Agentic CodingCRuns well31.9 tok/s8835 ms85K
ReasoningCRuns well31.9 tok/s7179 ms85K
RAGCRuns well31.9 tok/s11044 ms85K

Quantization options

How Solar Open 69B REAP i1 (69B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
26.9 GB
LowC42
Q3_K_S
3
33.8 GB
LowC43
NVFP4
4
38.6 GB
MediumC44
Q4_K_M
4
42.1 GB
MediumC45
Q5_K_M
5
49.7 GB
HighC47
Q6_K
6
56.6 GB
HighC48
Q8_0Best for your GPU
8
73.8 GB
Very HighC48
F16
16
141.5 GB
MaximumF0

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

アップグレードオプション

Solar Open 69B REAP i1を快適に動かすハードウェア

AMD Instinct MI300A 128GBコスパ重視
128 GB VRAM (+32)5300 GB/s (+3703)
C
Raises estimated decode speed by about 176%.88.1 tok/sデコード

Raises estimated decode speed by about 176%.

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

〜$12,000 MSRP

Frequently asked questions

Can RTX PRO 6000 Blackwell Server Edition 96GB run Solar Open 69B REAP i1?

Yes, RTX PRO 6000 Blackwell Server Edition 96GB can run Solar Open 69B REAP i1 with a C grade (Runs well). Expected decode speed: 31.9 tok/s.

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

Solar Open 69B REAP i1 (69B parameters) requires approximately 61.0 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 RTX PRO 6000 Blackwell Server Edition 96GB?

On RTX PRO 6000 Blackwell Server Edition 96GB, Solar Open 69B REAP i1 achieves approximately 31.9 tokens per second decode speed with a time-to-first-token of 6074ms using Q4_K_M quantization.

Can RTX PRO 6000 Blackwell Server Edition 96GB run Solar Open 69B REAP i1 for coding?

For coding workloads, Solar Open 69B REAP i1 on RTX PRO 6000 Blackwell Server Edition 96GB receives a C grade with 31.9 tok/s and 85K context.

What context window can Solar Open 69B REAP i1 use on RTX PRO 6000 Blackwell Server Edition 96GB?

On RTX PRO 6000 Blackwell Server Edition 96GB, Solar Open 69B REAP i1 can safely use up to 85K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RTX PRO 6000 Blackwell Server Edition 96GBSee all hardware for Solar Open 69B REAP i1
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