Can Baichuan M3 235B run on AMD Instinct MI325X 256GB?

YES — Runs Great

C53Usable

Estimated from fit model

Baichuan M3 235B needs ~197.4 GB VRAM. AMD Instinct MI325X 256GB has 256.0 GB. With Q4_K_M quantization, expect ~31 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: 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) — 197.4 GB, 30.6 tok/s, Runs well

197.4 GB required256.0 GB available

77% VRAM used

Fit status

Runs well

Decode

30.6 tok/s

TTFT

6336 ms

Safe context

50K

Memory

197.4 GB / 256.0 GB

Memory breakdown

Weights143.4 GB

KV Cache27.5 GB

Runtime0.9 GB

Headroom25.6 GB

See how fast it feels

See how fast it feelsBaichuan M3 235B on AMD Instinct MI325X 256GB
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: 30.6 tok/s decode · 6.3s TTFT (warm) · 76 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Runs well	30.6 tok/s	3456 ms	50K
Coding	C	Runs well	30.6 tok/s	6336 ms	50K
Agentic Coding	C	Tight fit	30.6 tok/s	9216 ms	50K
Reasoning	C	Runs well	30.6 tok/s	7488 ms	50K
RAG	C	Tight fit	30.6 tok/s	11520 ms	50K

Quantization options

How Baichuan M3 235B (235B params) fits at each quantization level on AMD Instinct MI325X 256GB (256.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	91.7 GB	Low	C44
Q3_K_S	3	115.2 GB	Low	C45
NVFP4	4

Get started

Copy-paste commands to run Baichuan M3 235B on your machine.

Run

lms load hf-mradermacher--baichuan-m3-235b-gguf && lms server start

Upgrade options

Hardware that runs Baichuan M3 235B well

AMD Instinct MI350X 288GBBudget pick

288 GB VRAM (+32)8000 GB/s (+2000)

Raises estimated decode speed by about 33%.40.7 tok/s decode

Raises estimated decode speed by about 33%.

~$8,000 MSRP

Frequently asked questions

Can AMD Instinct MI325X 256GB run Baichuan M3 235B?

Yes, AMD Instinct MI325X 256GB can run Baichuan M3 235B with a C grade (Runs well). Expected decode speed: 30.6 tok/s.

How much VRAM does Baichuan M3 235B need?

Baichuan M3 235B (235B parameters) requires approximately 197.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Baichuan M3 235B?

The recommended quantization for Baichuan M3 235B is Q4_K_M, which balances quality and memory efficiency.

What speed will Baichuan M3 235B run at on AMD Instinct MI325X 256GB?

On AMD Instinct MI325X 256GB, Baichuan M3 235B achieves approximately 30.6 tokens per second decode speed with a time-to-first-token of 6336ms using Q4_K_M quantization.

Can AMD Instinct MI325X 256GB run Baichuan M3 235B for coding?

For coding workloads, Baichuan M3 235B on AMD Instinct MI325X 256GB receives a C grade with 30.6 tok/s and 50K context.

What context window can Baichuan M3 235B use on AMD Instinct MI325X 256GB?

On AMD Instinct MI325X 256GB, Baichuan M3 235B can safely use up to 50K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for AMD Instinct MI325X 256GB See all hardware for Baichuan M3 235B

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