MacBook Pro M4 Max 48GBOpción económica
48 GB Unified (+16)
B
Este setup está bastante equilibrado para este modelo.87.8 tok/s decodificación
~$2,499 MSRP
Can Baichuan 7B run on AMD Instinct MI100 32GB?
YES — Runs Great
B69Good
Estimated from fit model
Baichuan 7B needs ~16.2 GB VRAM. AMD Instinct MI100 32GB has 32.0 GB. With Q4_K_M quantization, expect ~98 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.
Select quantization to explore
Q4_K_M (Medium quality) — 16.2 GB, 98.0 tok/s, Runs well
16.2 GB required32.0 GB available
51% VRAM used
Fit status
Runs well
Decode
98.0 tok/s
TTFT
1976 ms
Safe context
8K
Memory
16.2 GB / 32.0 GB
Memory breakdown
Weights4.3 GB
KV Cache7.8 GB
Runtime0.9 GB
Headroom3.2 GB
See how fast it feels
See how fast it feelsBaichuan 7B 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: 98.0 tok/s decode · 2.0s TTFT (warm) · 245 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 | B | Runs well | 98.0 tok/s | 1078 ms | 8K |
| Coding | B | Runs well | 98.0 tok/s | 1976 ms | 8K |
| Agentic Coding | A | Runs well | 98.0 tok/s | 2873 ms | 8K |
| Reasoning | B | Runs well | 98.0 tok/s | 2335 ms | 8K |
| RAG | A | Runs well | 98.0 tok/s | 3592 ms | 8K |
Quantization options
How Baichuan 7B (7B params) fits at each quantization level on AMD Instinct MI100 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B59 |
Q3_K_S | 3 | 3.4 GB | Low | B59 |
NVFP4 | 4 | 3.9 GB | Medium | B59 |
Q4_K_M | 4 | 4.3 GB | Medium | B60 |
Q5_K_M | 5 | 5.0 GB | High | B60 |
Q6_K | 6 | 5.7 GB | High | B60 |
Q8_0 | 8 | 7.5 GB | Very High | B61 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | B64 |
Get started
Copy-paste commands to run Baichuan 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "baichuan-inc/Baichuan-7B" \
--hf-file "Baichuan-7B-Q4_K_M.gguf" \
-c 4096 -ngl 99Opciones de mejora
Hardware que ejecuta bien Baichuan 7B
Frequently asked questions
Can AMD Instinct MI100 32GB run Baichuan 7B?
Yes, AMD Instinct MI100 32GB can run Baichuan 7B with a B grade (Runs well). Expected decode speed: 98.0 tok/s.
How much VRAM does Baichuan 7B need?
Baichuan 7B (7B parameters) requires approximately 16.2 GB of memory with Q4_K_M quantization.
What is the best quantization for Baichuan 7B?
The recommended quantization for Baichuan 7B is Q4_K_M, which balances quality and memory efficiency.
What speed will Baichuan 7B run at on AMD Instinct MI100 32GB?
On AMD Instinct MI100 32GB, Baichuan 7B achieves approximately 98.0 tokens per second decode speed with a time-to-first-token of 1976ms using Q4_K_M quantization.
Can AMD Instinct MI100 32GB run Baichuan 7B for coding?
For coding workloads, Baichuan 7B on AMD Instinct MI100 32GB receives a B grade with 98.0 tok/s and 8K context.
What context window can Baichuan 7B use on AMD Instinct MI100 32GB?
On AMD Instinct MI100 32GB, Baichuan 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Embed this result▼
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<iframe src="https://willitrunai.com/embed/baichuan-7b-on-instinct-mi100-32gb" 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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