Will It Run AI

Can Vicuna 13B run on AMD Instinct MI300X 192GB?

YES — Runs Great

B67Good
Estimated from fit model

Vicuna 13B needs ~40.2 GB VRAM. AMD Instinct MI300X 192GB has 192.0 GB. With Q4_K_M quantization, expect ~182 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 40.2 GB, 182.0 tok/s, Runs well
40.2 GB required192.0 GB available
21% VRAM used

Fit status

Runs well

Decode

182.0 tok/s

TTFT

1064 ms

Safe context

4K

Memory

40.2 GB / 192.0 GB

Memory breakdown

Weights7.9 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom19.2 GB

See how fast it feels

See how fast it feelsVicuna 13B on AMD Instinct MI300X 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: 182.0 tok/s decode · 1.1s TTFT (warm) · 455 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 well182.0 tok/s580 ms4K
CodingBRuns well182.0 tok/s1064 ms4K
Agentic CodingBRuns well182.0 tok/s1547 ms4K
ReasoningBRuns well182.0 tok/s1257 ms4K
RAGBRuns well182.0 tok/s1934 ms4K

Quantization options

How Vicuna 13B (13B params) fits at each quantization level on AMD Instinct MI300X 192GB (192.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB58
Q3_K_S
3
6.4 GB
LowB58
NVFP4
4
7.3 GB
MediumB58
Q4_K_M
4
7.9 GB
MediumB58
Q5_K_M
5
9.4 GB
HighB58
Q6_K
6
10.7 GB
HighB58
Q8_0
8
13.9 GB
Very HighB58
F16Best for your GPU
16
26.7 GB
MaximumB59

Get started

Copy-paste commands to run Vicuna 13B on your machine.

Run

ollama run vicuna:13b

Frequently asked questions

Can AMD Instinct MI300X 192GB run Vicuna 13B?

Yes, AMD Instinct MI300X 192GB can run Vicuna 13B with a B grade (Runs well). Expected decode speed: 182.0 tok/s.

How much VRAM does Vicuna 13B need?

Vicuna 13B (13B parameters) requires approximately 40.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Vicuna 13B?

The recommended quantization for Vicuna 13B is Q4_K_M, which balances quality and memory efficiency.

What speed will Vicuna 13B run at on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Vicuna 13B achieves approximately 182.0 tokens per second decode speed with a time-to-first-token of 1064ms using Q4_K_M quantization.

Can AMD Instinct MI300X 192GB run Vicuna 13B for coding?

For coding workloads, Vicuna 13B on AMD Instinct MI300X 192GB receives a B grade with 182.0 tok/s and 4K context.

What context window can Vicuna 13B use on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Vicuna 13B can safely use up to 4K tokens of context. The model's official context limit is 4K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI300X 192GBSee all hardware for Vicuna 13B
Embed this result▼

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

<iframe src="https://willitrunai.com/embed/vicuna-13b-on-instinct-mi300x-192gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: