Can Baichuan 13B run on AMD Instinct MI100 32GB?

YES — Runs Great

A73Great
Estimated from fit model

Baichuan 13B needs ~25.7 GB VRAM. AMD Instinct MI100 32GB has 32.0 GB. With Q5_K_M quantization, expect ~87 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
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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

Q5_K_M (High quality) 25.7 GB, 87.0 tok/s, Runs well
25.7 GB required32.0 GB available
80% VRAM used

Fit status

Runs well

Decode

87.0 tok/s

TTFT

2226 ms

Safe context

8K

Memory

25.7 GB / 32.0 GB

Memory breakdown

Weights9.4 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom3.2 GB

See how fast it feels

See how fast it feelsBaichuan 13B on AMD Instinct MI100 32GB
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: 87.0 tok/s decode · 2.2s TTFT (warm) · 218 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
ChatARuns well87.0 tok/s1214 ms8K
CodingARuns well87.0 tok/s2226 ms8K
Agentic CodingCVery compromised (needs ~1.5 GB host RAM)45.8 tok/s6155 ms8K
ReasoningARuns well87.0 tok/s2630 ms8K
RAGCVery compromised (needs ~1.5 GB host RAM)45.8 tok/s7693 ms8K

Quantization options

How Baichuan 13B (13B params) fits at each quantization level on AMD Instinct MI100 32GB (32.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB60
Q3_K_S
3
6.4 GB
LowB60
NVFP4
4
7.3 GB
MediumB61
Q4_K_M
4
7.9 GB
MediumB61
Q5_K_M
5
9.4 GB
HighB62
Q6_K
6
10.7 GB
HighB62
Q8_0
8
13.9 GB
Very HighB64
F16Best for your GPU
16
26.7 GB
MaximumB65

Get started

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

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "baichuan-inc/Baichuan-13B-Chat" \ --hf-file "Baichuan-13B-Chat-Q5_K_M.gguf" \ -c 4096 -ngl 99

Your hardware

More models your AMD Instinct MI100 32GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS120.7 tok/s
AlibabaQwen 3.5 27B27BS52.3 tok/s
AlibabaQwen 3.6 27B27BS32.6 tok/s
AlibabaQwen 3.6 35B A3B35BS101.4 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS124.8 tok/s

Frequently asked questions

Can AMD Instinct MI100 32GB run Baichuan 13B?

Yes, AMD Instinct MI100 32GB can run Baichuan 13B with a A grade (Runs well). Expected decode speed: 87.0 tok/s.

How much VRAM does Baichuan 13B need?

Baichuan 13B (13B parameters) requires approximately 25.7 GB of memory with Q5_K_M quantization.

What is the best quantization for Baichuan 13B?

The recommended quantization for Baichuan 13B is Q5_K_M, which balances quality and memory efficiency.

What speed will Baichuan 13B run at on AMD Instinct MI100 32GB?

On AMD Instinct MI100 32GB, Baichuan 13B achieves approximately 87.0 tokens per second decode speed with a time-to-first-token of 2226ms using Q5_K_M quantization.

Can AMD Instinct MI100 32GB run Baichuan 13B for coding?

For coding workloads, Baichuan 13B on AMD Instinct MI100 32GB receives a A grade with 87.0 tok/s and 8K context.

What context window can Baichuan 13B use on AMD Instinct MI100 32GB?

On AMD Instinct MI100 32GB, Baichuan 13B 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 AMD Instinct MI100 32GBSee all hardware for Baichuan 13B
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