Will It Run AI

Can Yi 34B Chat run on AMD Instinct MI350X 288GB?

YES — Runs Great

C47Usable
Estimated from fit model

Yi 34B Chat needs ~54.1 GB VRAM. AMD Instinct MI350X 288GB has 288.0 GB. With Q4_K_M quantization, expect ~282 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) — 54.1 GB, 305.7 tok/s, Runs well
54.1 GB required288.0 GB available
19% VRAM used

Fit status

Runs well

Decode

305.7 tok/s

TTFT

633 ms

Safe context

200K

Memory

54.1 GB / 288.0 GB

Memory breakdown

Weights20.7 GB
KV Cache3.7 GB
Runtime0.9 GB
Headroom28.8 GB

See how fast it feels

See how fast it feelsYi 34B Chat on AMD Instinct MI350X 288GB
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: 305.7 tok/s decode · 633ms TTFT (warm) · 764 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 well305.7 tok/s350 ms200K
CodingCRuns well281.6 tok/s688 ms200K
Agentic CodingCRuns well305.7 tok/s921 ms200K
ReasoningCRuns well305.7 tok/s748 ms200K
RAGCRuns well305.7 tok/s1151 ms200K

Quantization options

How Yi 34B Chat (34B params) fits at each quantization level on AMD Instinct MI350X 288GB (288.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
13.3 GB
LowD38
Q3_K_S
3
16.7 GB
LowD38
NVFP4
4
19.0 GB
MediumD38
Q4_K_M
4
20.7 GB
MediumD38
Q5_K_M
5
24.5 GB
HighD39
Q6_K
6
27.9 GB
HighD39
Q8_0
8
36.4 GB
Very HighD39
F16Best for your GPU
16
69.7 GB
MaximumC42

Get started

Copy-paste commands to run Yi 34B Chat on your machine.

Run

lms load Yi-34B-Chat && lms server start

Frequently asked questions

Can AMD Instinct MI350X 288GB run Yi 34B Chat?

Yes, AMD Instinct MI350X 288GB can run Yi 34B Chat with a C grade (Runs well). Expected decode speed: 281.6 tok/s.

How much VRAM does Yi 34B Chat need?

Yi 34B Chat (34B parameters) requires approximately 54.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Yi 34B Chat?

The recommended quantization for Yi 34B Chat is Q4_K_M, which balances quality and memory efficiency.

What speed will Yi 34B Chat run at on AMD Instinct MI350X 288GB?

On AMD Instinct MI350X 288GB, Yi 34B Chat achieves approximately 281.6 tokens per second decode speed with a time-to-first-token of 688ms using Q4_K_M quantization.

Can AMD Instinct MI350X 288GB run Yi 34B Chat for coding?

For coding workloads, Yi 34B Chat on AMD Instinct MI350X 288GB receives a C grade with 281.6 tok/s and 200K context.

What context window can Yi 34B Chat use on AMD Instinct MI350X 288GB?

On AMD Instinct MI350X 288GB, Yi 34B Chat can safely use up to 200K tokens of context. The model's official context limit is 200K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI350X 288GBSee all hardware for Yi 34B Chat
Embed this result▼

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

<iframe src="https://willitrunai.com/embed/yi-34b-chat-on-instinct-mi350x-288gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: