Will It Run AI

Can Solar Open 100B i1 run on NVIDIA GB200 192GB?

YES — Runs Great

C52Usable
Estimated from fit model

Solar Open 100B i1 needs ~93.1 GB VRAM. NVIDIA GB200 192GB has 192.0 GB. With Q4_K_M quantization, expect ~110 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) — 93.1 GB, 110.2 tok/s, Runs well
93.1 GB required192.0 GB available
48% VRAM used

Fit status

Runs well

Decode

110.2 tok/s

TTFT

1757 ms

Safe context

151K

Memory

93.1 GB / 192.0 GB

Memory breakdown

Weights61.0 GB
KV Cache11.7 GB
Runtime1.2 GB
Headroom19.2 GB

See how fast it feels

See how fast it feelsSolar Open 100B i1 on NVIDIA GB200 192GB
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: 110.2 tok/s decode · 1.8s TTFT (warm) · 275 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 well110.2 tok/s959 ms151K
CodingCRuns well110.2 tok/s1757 ms151K
Agentic CodingCRuns well110.2 tok/s2556 ms151K
ReasoningCRuns well110.2 tok/s2077 ms151K
RAGCRuns well110.2 tok/s3195 ms151K

Quantization options

How Solar Open 100B i1 (100B params) fits at each quantization level on NVIDIA GB200 192GB (192.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
39.0 GB
LowD40
Q3_K_S
3
49.0 GB
LowC41
NVFP4
4
56.0 GB
MediumC42
Q4_K_M
4
61.0 GB
MediumC42
Q5_K_M
5
72.0 GB
HighC44
Q6_K
6
82.0 GB
HighC45
Q8_0Best for your GPU
8
107.0 GB
Very HighC47
F16
16
205.0 GB
MaximumF0

Get started

Copy-paste commands to run Solar Open 100B i1 on your machine.

Run

lms load hf-mradermacher--solar-open-100b-i1-gguf && lms server start

Frequently asked questions

Can NVIDIA GB200 192GB run Solar Open 100B i1?

Yes, NVIDIA GB200 192GB can run Solar Open 100B i1 with a C grade (Runs well). Expected decode speed: 110.2 tok/s.

How much VRAM does Solar Open 100B i1 need?

Solar Open 100B i1 (100B parameters) requires approximately 93.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Solar Open 100B i1?

The recommended quantization for Solar Open 100B i1 is Q4_K_M, which balances quality and memory efficiency.

What speed will Solar Open 100B i1 run at on NVIDIA GB200 192GB?

On NVIDIA GB200 192GB, Solar Open 100B i1 achieves approximately 110.2 tokens per second decode speed with a time-to-first-token of 1757ms using Q4_K_M quantization.

Can NVIDIA GB200 192GB run Solar Open 100B i1 for coding?

For coding workloads, Solar Open 100B i1 on NVIDIA GB200 192GB receives a C grade with 110.2 tok/s and 151K context.

What context window can Solar Open 100B i1 use on NVIDIA GB200 192GB?

On NVIDIA GB200 192GB, Solar Open 100B i1 can safely use up to 151K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for NVIDIA GB200 192GBSee all hardware for Solar Open 100B i1
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