Can Cerebras-GPT 13B run on AMD Instinct MI100 32GB?
YES — Runs Great
Cerebras-GPT 13B needs ~23.5 GB VRAM. AMD Instinct MI100 32GB has 32.0 GB. With Q5_K_M quantization, expect ~87 tok/s.
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
Fit status
Runs well
Decode
87.0 tok/s
TTFT
2226 ms
Safe context
30K
Memory
23.5 GB / 32.0 GB
Memory breakdown
See how fast it feels
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 | A | Runs well | 87.0 tok/s | 1214 ms | 30K |
| Coding | A | Runs well | 87.0 tok/s | 2226 ms | 30K |
| Agentic Coding | B | Runs with offload (needs ~0.4 GB host RAM) | 60.0 tok/s | 4691 ms | 30K |
| Reasoning | A | Runs well | 87.0 tok/s | 2630 ms | 30K |
| RAG | B | Runs with offload (needs ~0.4 GB host RAM) | 60.0 tok/s | 5864 ms | 30K |
Quantization options
How Cerebras-GPT 13B (13B params) fits at each quantization level on AMD Instinct MI100 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.1 GB | Low | B60 |
Q3_K_S | 3 | 6.4 GB | Low | B60 |
NVFP4 | 4 | 7.3 GB | Medium | B61 |
Q4_K_M | 4 | 7.9 GB | Medium | B61 |
Q5_K_M | 5 | 9.4 GB | High | B62 |
Q6_K | 6 | 10.7 GB | High | B62 |
Q8_0 | 8 | 13.9 GB | Very High | B64 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | B65 |
Get started
Copy-paste commands to run Cerebras-GPT 13B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "cerebras/Cerebras-GPT-13B" \
--hf-file "Cerebras-GPT-13B-Q5_K_M.gguf" \
-c 4096 -ngl 99Your hardware
More models your AMD Instinct MI100 32GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 120.7 tok/s | ||
| 27B | S | 52.3 tok/s | ||
| 27B | S | 52.5 tok/s | ||
| 35B | S | 101.4 tok/s | ||
| 30B | S | 124.8 tok/s |
Frequently asked questions
Can AMD Instinct MI100 32GB run Cerebras-GPT 13B?
Yes, AMD Instinct MI100 32GB can run Cerebras-GPT 13B with a A grade (Runs well). Expected decode speed: 87.0 tok/s.
How much VRAM does Cerebras-GPT 13B need?
Cerebras-GPT 13B (13B parameters) requires approximately 23.5 GB of memory with Q5_K_M quantization.
What is the best quantization for Cerebras-GPT 13B?
The recommended quantization for Cerebras-GPT 13B is Q5_K_M, which balances quality and memory efficiency.
What speed will Cerebras-GPT 13B run at on AMD Instinct MI100 32GB?
On AMD Instinct MI100 32GB, Cerebras-GPT 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 Cerebras-GPT 13B for coding?
For coding workloads, Cerebras-GPT 13B on AMD Instinct MI100 32GB receives a A grade with 87.0 tok/s and 30K context.
What context window can Cerebras-GPT 13B use on AMD Instinct MI100 32GB?
On AMD Instinct MI100 32GB, Cerebras-GPT 13B can safely use up to 30K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Embed this result▼
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<iframe src="https://willitrunai.com/embed/cerebras-gpt-13b-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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