Can Solar Open 69B REAP i1 run on NVIDIA A16 64GB?

YES — Tight Fit

C47Usable

Estimated from fit model

Solar Open 69B REAP i1 needs ~57.8 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~11 tok/s.

Runtime: OllamaCapacity: TightBandwidth: MediumStack: BasicBottleneck: Balanced

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) — 57.8 GB, 11.1 tok/s, Tight fit

57.8 GB required64.0 GB available

90% VRAM used

Fit status

Tight fit

Decode

11.1 tok/s

TTFT

17412 ms

Safe context

28K

Memory

57.8 GB / 64.0 GB

Memory breakdown

Weights42.1 GB

KV Cache8.1 GB

Runtime1.2 GB

Headroom6.4 GB

See how fast it feels

See how fast it feelsSolar Open 69B REAP i1 on NVIDIA A16 64GB
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: 11.1 tok/s decode · 17.4s TTFT (warm) · 28 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Tight fit	11.1 tok/s	9497 ms	28K
Coding	C	Tight fit	11.1 tok/s	17412 ms	28K
Agentic Coding	C	Runs with offload (needs ~1.2 GB host RAM)	7.9 tok/s	35869 ms	28K
Reasoning	C	Tight fit	11.1 tok/s	20577 ms	28K
RAG	C	Runs with offload (needs ~1.2 GB host RAM)	7.9 tok/s	44836 ms

Quantization options

How Solar Open 69B REAP i1 (69B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	26.9 GB	Low	C46
Q3_K_S	3	33.8 GB	Low	C48
NVFP4	4

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 options

Hardware that runs Solar Open 69B REAP i1 well

RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pick

96 GB VRAM (+32)1792 GB/s (+1192)

Raises estimated decode speed by about 223%.35.8 tok/s decode

Raises estimated decode speed by about 223%.

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

~$9,999 MSRP

RTX PRO 6000 Blackwell Server Edition 96GBBest value

96 GB VRAM (+32)1597 GB/s (+997)

Raises estimated decode speed by about 187%.31.9 tok/s decode

Raises estimated decode speed by about 187%.

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

~$9,999 MSRP

NVIDIA H20 96GBNVIDIA upgrade

96 GB VRAM (+32)4000 GB/s (+3400)

Raises estimated decode speed by about 594%.77 tok/s decode

Raises estimated decode speed by about 594%.

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

~$12,000 MSRP

Frequently asked questions

Can NVIDIA A16 64GB run Solar Open 69B REAP i1?

Yes, NVIDIA A16 64GB can run Solar Open 69B REAP i1 with a C grade (Tight fit). Expected decode speed: 11.1 tok/s.

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

Solar Open 69B REAP i1 (69B parameters) requires approximately 57.8 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 NVIDIA A16 64GB?

On NVIDIA A16 64GB, Solar Open 69B REAP i1 achieves approximately 11.1 tokens per second decode speed with a time-to-first-token of 17412ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Solar Open 69B REAP i1 for coding?

For coding workloads, Solar Open 69B REAP i1 on NVIDIA A16 64GB receives a C grade with 11.1 tok/s and 28K context.

What context window can Solar Open 69B REAP i1 use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Solar Open 69B REAP i1 can safely use up to 28K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for NVIDIA A16 64GB See all hardware for Solar Open 69B REAP i1

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