Cerebras-GPT 13B needs ~29.9 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q5_K_M quantization, expect ~146 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
Runs well
Decode
146.2 tok/s
TTFT
1324 ms
Safe context
124K
Memory
29.9 GB / 96.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 146.2 tok/s | 722 ms | 124K |
| Coding | B | Runs well | 146.2 tok/s | 1324 ms | 124K |
| Agentic Coding | B | Runs well | 146.2 tok/s | 1926 ms | 124K |
| Reasoning | B | Runs well | 146.2 tok/s | 1565 ms | 124K |
| RAG | B | Runs well | 146.2 tok/s | 2408 ms | 124K |
How Cerebras-GPT 13B (13B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.1 GB | Low | B55 |
Q3_K_S | 3 | 6.4 GB | Low | B55 |
NVFP4 | 4 | 7.3 GB | Medium | B55 |
Q4_K_M | 4 | 7.9 GB | Medium | B55 |
Q5_K_M | 5 | 9.4 GB | High | B55 |
Q6_K | 6 | 10.7 GB | High | B56 |
Q8_0 | 8 | 13.9 GB | Very High | B56 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | B58 |
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 99Yes, RTX PRO 6000 Blackwell Server Edition 96GB can run Cerebras-GPT 13B with a B grade (Runs well). Expected decode speed: 146.2 tok/s.
Cerebras-GPT 13B (13B parameters) requires approximately 29.9 GB of memory with Q5_K_M quantization.
The recommended quantization for Cerebras-GPT 13B is Q5_K_M, which balances quality and memory efficiency.
On RTX PRO 6000 Blackwell Server Edition 96GB, Cerebras-GPT 13B achieves approximately 146.2 tokens per second decode speed with a time-to-first-token of 1324ms using Q5_K_M quantization.
For coding workloads, Cerebras-GPT 13B on RTX PRO 6000 Blackwell Server Edition 96GB receives a B grade with 146.2 tok/s and 124K context.
On RTX PRO 6000 Blackwell Server Edition 96GB, Cerebras-GPT 13B can safely use up to 124K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
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Preview: