Can Solar 7B run on RTX 3080 10GB?

YES — Tight Fit

A75Great

○Estimated from fit model

Solar 7B needs ~9.4 GB VRAM. RTX 3080 10GB has 10.0 GB. With Q4_K_M quantization, expect ~98 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) — 9.4 GB, 98.0 tok/s, Tight fit

9.4 GB required10.0 GB available

94% VRAM used

Fit status

Tight fit

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

Memory

9.4 GB / 10.0 GB

Memory breakdown

Weights4.3 GB

KV Cache2.9 GB

Runtime1.2 GB

Headroom1.0 GB

See how fast it feels

See how fast it feelsSolar 7B on RTX 3080 10GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
 - Speed = 60 mph (miles per hour)
 - Time = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
 Distance = 60 mph x 2.5 h
 = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
 - First half: 1.25 hours at 60 mph = 75 miles
 - Stop: 20 minutes (no distance)
 - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 98.0 tok/s decode · 2.0s TTFT (warm) · 245 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	98.0 tok/s	1078 ms	8K
Coding	A	Tight fit	98.0 tok/s	1976 ms	8K
Agentic Coding	F	Too heavy	70.2 tok/s	4012 ms	8K
Reasoning	A	Tight fit	98.0 tok/s	2335 ms	8K
RAG	F	Too heavy	70.2 tok/s	5015 ms	8K

Quantization options

How Solar 7B (7B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	A71
Q3_K_S	3	3.4 GB	Low	A72
NVFP4	4	3.9 GB	Medium	A73
Q4_K_M	4	4.3 GB	Medium	A74
Q5_K_M	5	5.0 GB	High	A73
Q6_KBest for your GPU	6	5.7 GB	High	A73
Q8_0	8	7.5 GB	Very High	F0
F16	16	14.3 GB	Maximum	F0

Get started

Copy-paste commands to run Solar 7B on your machine.

Run

lms load Solar-7B && lms server start

Your hardware

More models your RTX 3080 10GB can run

Model	Params	Grade	Decode
👁 Alibaba Qwen 3.5 9B	9B	S	113.1 tok/s
👁 Alibaba Qwen 3 8B	8B	S	112 tok/s
👁 NVIDIA Nemotron Nano 8B	8B	S	112 tok/s
👁 InternLM InternVL2 8B	8B	S	112 tok/s
👁 Mistral Ministral 3 8B	8B	A	112 tok/s

Frequently asked questions

See all results for RTX 3080 10GB See all hardware for Solar 7B

URL: https://willitrunai.com/can-run/solar-7b-on-rtx-3080-10gb