Will It Run AI

Can BaichuanMed OCR 72B i1 run on AMD Instinct MI210 64GB?

YES — Tight Fit

C49Usable
Estimated from fit model

BaichuanMed OCR 72B i1 needs ~59.7 GB VRAM. AMD Instinct MI210 64GB has 64.0 GB. With Q4_K_M quantization, expect ~25 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: 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

Q4_K_M (Medium quality) 59.7 GB, 25.4 tok/s, Tight fit
59.7 GB required64.0 GB available
93% VRAM used

Fit status

Tight fit

Decode

25.4 tok/s

TTFT

7634 ms

Safe context

24K

Memory

59.7 GB / 64.0 GB

Memory breakdown

Weights43.9 GB
KV Cache8.4 GB
Runtime0.9 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsBaichuanMed OCR 72B i1 on AMD Instinct MI210 64GB
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: 25.4 tok/s decode · 7.6s TTFT (warm) · 63 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCTight fit25.4 tok/s4164 ms24K
CodingCTight fit25.4 tok/s7634 ms24K
Agentic CodingDRuns with offload (needs ~2.6 GB host RAM)16.7 tok/s16870 ms24K
ReasoningCTight fit25.4 tok/s9022 ms24K
RAGDRuns with offload (needs ~2.6 GB host RAM)16.7 tok/s21087 ms24K

Quantization options

How BaichuanMed OCR 72B i1 (72B params) fits at each quantization level on AMD Instinct MI210 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
28.1 GB
LowC46
Q3_K_S
3
35.3 GB
LowC47
NVFP4
4
40.3 GB
MediumC47
Q4_K_M
4
43.9 GB
MediumC47
Q5_K_MBest for your GPU
5
51.8 GB
HighC47
Q6_K
6
59.0 GB
HighF0
Q8_0
8
77.0 GB
Very HighF0
F16
16
147.6 GB
MaximumF0

Get started

Copy-paste commands to run BaichuanMed OCR 72B i1 on your machine.

Run

lms load hf-mradermacher--baichuanmed-ocr-72b-i1-gguf && lms server start

升级选项

能流畅运行 BaichuanMed OCR 72B i1 的硬件

Frequently asked questions

Can AMD Instinct MI210 64GB run BaichuanMed OCR 72B i1?

Yes, AMD Instinct MI210 64GB can run BaichuanMed OCR 72B i1 with a C grade (Tight fit). Expected decode speed: 25.4 tok/s.

How much VRAM does BaichuanMed OCR 72B i1 need?

BaichuanMed OCR 72B i1 (72B parameters) requires approximately 59.7 GB of memory with Q4_K_M quantization.

What is the best quantization for BaichuanMed OCR 72B i1?

The recommended quantization for BaichuanMed OCR 72B i1 is Q4_K_M, which balances quality and memory efficiency.

What speed will BaichuanMed OCR 72B i1 run at on AMD Instinct MI210 64GB?

On AMD Instinct MI210 64GB, BaichuanMed OCR 72B i1 achieves approximately 25.4 tokens per second decode speed with a time-to-first-token of 7634ms using Q4_K_M quantization.

Can AMD Instinct MI210 64GB run BaichuanMed OCR 72B i1 for coding?

For coding workloads, BaichuanMed OCR 72B i1 on AMD Instinct MI210 64GB receives a C grade with 25.4 tok/s and 24K context.

What context window can BaichuanMed OCR 72B i1 use on AMD Instinct MI210 64GB?

On AMD Instinct MI210 64GB, BaichuanMed OCR 72B i1 can safely use up to 24K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

What should I upgrade first if BaichuanMed OCR 72B i1 feels slow on AMD Instinct MI210 64GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

See all results for AMD Instinct MI210 64GBSee all hardware for BaichuanMed OCR 72B i1
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