OLMo 2 13B needs ~16.1 GB VRAM. RTX PRO 5000 Blackwell 48GB has 48.0 GB. With Q4_K_M quantization, expect ~154 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
153.8 tok/s
TTFT
1259 ms
Safe context
33K
Memory
16.1 GB / 48.0 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 | A | Runs well | 153.8 tok/s | 687 ms | 33K |
| Coding | A | Runs well | 153.8 tok/s | 1259 ms | 33K |
| Agentic Coding | A | Runs well | 153.8 tok/s | 1831 ms | 33K |
| Reasoning | A | Runs well | 153.8 tok/s | 1488 ms | 33K |
| RAG | A | Runs well | 153.8 tok/s | 2289 ms | 33K |
How OLMo 2 13B (13B params) fits at each quantization level on RTX PRO 5000 Blackwell 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.1 GB | Low | B69 |
Q3_K_S | 3 | 6.4 GB | Low | B69 |
NVFP4 | 4 | 7.3 GB | Medium | B69 |
Q4_K_M | 4 | 7.9 GB | Medium | B69 |
Q5_K_M | 5 | 9.4 GB | High | B70 |
Q6_K | 6 | 10.7 GB | High | B70 |
Q8_0 | 8 | 13.9 GB | Very High | A71 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | A75 |
Copy-paste commands to run OLMo 2 13B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "allenai/OLMo-2-13B-Instruct" \
--hf-file "OLMo-2-13B-Instruct-Q4_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 170.7 tok/s | |
| Qwen 3.5 27B | 27B | S | 74 tok/s | |
| Qwen 3.6 27B | 27B | S | 46.1 tok/s | |
| Qwen 3.6 35B A3B | 35B | S | 143.5 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 176.6 tok/s |
Yes, RTX PRO 5000 Blackwell 48GB can run OLMo 2 13B with a A grade (Runs well). Expected decode speed: 153.8 tok/s.
OLMo 2 13B (13B parameters) requires approximately 16.1 GB of memory with Q4_K_M quantization.
The recommended quantization for OLMo 2 13B is Q4_K_M, which balances quality and memory efficiency.
On RTX PRO 5000 Blackwell 48GB, OLMo 2 13B achieves approximately 153.8 tokens per second decode speed with a time-to-first-token of 1259ms using Q4_K_M quantization.
For coding workloads, OLMo 2 13B on RTX PRO 5000 Blackwell 48GB receives a A grade with 153.8 tok/s and 33K context.
On RTX PRO 5000 Blackwell 48GB, OLMo 2 13B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/olmo-2-13b-on-rtx-pro-5000-blackwell-48gb" 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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