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.
Operating mode
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.
Select quantization to explore
Fit status
Tight fit
Decode
25.4 tok/s
TTFT
7634 ms
Safe context
24K
Memory
59.7 GB / 64.0 GB
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.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 25.4 tok/s | 4164 ms | 24K |
| Coding | C | Tight fit | 25.4 tok/s | 7634 ms | 24K |
| Agentic Coding | D | Runs with offload (needs ~2.6 GB host RAM) | 16.7 tok/s | 16870 ms | 24K |
| Reasoning | C | Tight fit | 25.4 tok/s | 9022 ms | 24K |
| RAG | D | Runs with offload (needs ~2.6 GB host RAM) | 16.7 tok/s | 21087 ms | 24K |
Inference speed
Estimated decode speed (tokens/sec) for BaichuanMed OCR 72B i1 at Q4_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is MacBook Pro M4 Max 128GB at ~14 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 13.7 | Fits |
2× RX 7900 XTX 24GB | 48 GB | Q4_K_M | 13.4 | Too big |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 12.7 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 10.6 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 10.0 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 9.4 | Too big |
 2× RTX 4090 24GB | 48 GB | Q4_K_M | 7.1 | Too big |
| RTX 5090 32GB | 32 GB | Q4_K_M | 6.5 | Too big |
| 2× RTX 3090 24GB | 48 GB | Q4_K_M | 6.5 | Too big |
| 4× RTX 3060 12GB | 48 GB | Q4_K_M | 5.7 | Too big |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 4.4 | Too big |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 3.8 | Too big |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 3.4 | Too big |
| RTX 4090 24GB | 24 GB | Q4_K_M | 2.6 | Too big |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 2.4 | Too big |
| RTX 3090 24GB | 24 GB | Q4_K_M | 2.2 | Too big |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 2.1 | Too big |
| RTX 4070 12GB | 12 GB | Q4_K_M | 2.0 | Too big |
| RTX 3060 12GB | 12 GB | Q4_K_M | 2.0 | Too big |
| RTX 4060 8GB | 8 GB | Q4_K_M | 2.0 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How BaichuanMed OCR 72B i1 (72B params) fits at each quantization level on AMD Instinct MI210 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | C46 |
Q3_K_S | 3 | 35.3 GB | Low | C47 |
NVFP4 | 4 | 40.3 GB | Medium | C47 |
Q4_K_M | 4 | 43.9 GB | Medium | C47 |
Q5_K_MBest for your GPU | 5 | 51.8 GB | High | C47 |
Q6_K | 6 | 59.0 GB | High | F0 |
Q8_0 | 8 | 77.0 GB | Very High | F0 |
F16 | 16 | 147.6 GB | Maximum | F0 |
Copy-paste commands to run BaichuanMed OCR 72B i1 on your machine.
Run
lms load hf-mradermacher--baichuanmed-ocr-72b-i1-gguf && lms server startUpgrade options
Raises estimated decode speed by about 233%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
Raises estimated decode speed by about 124%.
Adds memory headroom for longer context windows and future model growth.
~$15,000 MSRP
Raises estimated decode speed by about 270%.
Adds memory headroom for longer context windows and future model growth.
~$15,000 MSRP
Yes, AMD Instinct MI210 64GB can run BaichuanMed OCR 72B i1 with a C grade (Tight fit). Expected decode speed: 25.4 tok/s.
BaichuanMed OCR 72B i1 (72B parameters) requires approximately 59.7 GB of memory with Q4_K_M quantization.
The recommended quantization for BaichuanMed OCR 72B i1 is Q4_K_M, which balances quality and memory efficiency.
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.
For coding workloads, BaichuanMed OCR 72B i1 on AMD Instinct MI210 64GB receives a C grade with 25.4 tok/s and 24K context.
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.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-mradermacher--baichuanmed-ocr-72b-i1-gguf-on-instinct-mi210-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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