Will It Run AI

Can Mistral 7B Instruct v0.3 run on RTX 3080 10GB?

YES — Runs Great

B69Good
Estimated from fit model

Mistral 7B Instruct v0.3 needs ~8.1 GB VRAM. RTX 3080 10GB has 10.0 GB. With Q4_K_M quantization, expect ~84 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
Share:

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) 8.1 GB, 84.0 tok/s, Runs well
8.1 GB required10.0 GB available
81% VRAM used

Fit status

Runs well

Decode

84.0 tok/s

TTFT

2305 ms

Safe context

8K

Memory

8.1 GB / 10.0 GB

Memory breakdown

Weights4.3 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom1.0 GB

See how fast it feels

See how fast it feelsMistral 7B Instruct v0.3 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: 84.0 tok/s decode · 2.3s TTFT (warm) · 210 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
ChatBRuns well84.0 tok/s1257 ms8K
CodingBRuns well84.0 tok/s2305 ms8K
Agentic CodingBRuns with offload (needs ~0 GB host RAM)84.0 tok/s3352 ms8K
ReasoningBRuns well84.0 tok/s2724 ms8K
RAGBRuns with offload (needs ~0 GB host RAM)84.0 tok/s4190 ms8K

Quantization options

How Mistral 7B Instruct v0.3 (7B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB63
Q3_K_S
3
3.4 GB
LowB64
NVFP4
4
3.9 GB
MediumB65
Q4_K_M
4
4.3 GB
MediumB65
Q5_K_M
5
5.0 GB
HighB65
Q6_KBest for your GPU
6
5.7 GB
HighB65
Q8_0
8
7.5 GB
Very HighF0
F16
16
14.3 GB
MaximumF0

Get started

Copy-paste commands to run Mistral 7B Instruct v0.3 on your machine.

Run

lms load Mistral-7B-Instruct-v0.3 && lms server start

升级选项

能流畅运行 Mistral 7B Instruct v0.3 的硬件

Frequently asked questions

Can RTX 3080 10GB run Mistral 7B Instruct v0.3?

Yes, RTX 3080 10GB can run Mistral 7B Instruct v0.3 with a B grade (Runs well). Expected decode speed: 84.0 tok/s.

How much VRAM does Mistral 7B Instruct v0.3 need?

Mistral 7B Instruct v0.3 (7B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Mistral 7B Instruct v0.3?

The recommended quantization for Mistral 7B Instruct v0.3 is Q4_K_M, which balances quality and memory efficiency.

What speed will Mistral 7B Instruct v0.3 run at on RTX 3080 10GB?

On RTX 3080 10GB, Mistral 7B Instruct v0.3 achieves approximately 84.0 tokens per second decode speed with a time-to-first-token of 2305ms using Q4_K_M quantization.

Can RTX 3080 10GB run Mistral 7B Instruct v0.3 for coding?

For coding workloads, Mistral 7B Instruct v0.3 on RTX 3080 10GB receives a B grade with 84.0 tok/s and 8K context.

What context window can Mistral 7B Instruct v0.3 use on RTX 3080 10GB?

On RTX 3080 10GB, Mistral 7B Instruct v0.3 can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for RTX 3080 10GBSee all hardware for Mistral 7B Instruct v0.3
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/mistral-7b-instruct-v0.3-on-rtx-3080-10gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: