OLMo 2 32B needs ~32.6 GB VRAM. NVIDIA H100 PCIe 80GB has 80.0 GB. With Q4_K_M quantization, expect ~93 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
93.0 tok/s
TTFT
2083 ms
Safe context
4K
Memory
32.6 GB / 80.0 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 | 93.0 tok/s | 1136 ms | 4K |
| Coding | A | Runs well | 93.0 tok/s | 2083 ms | 4K |
| Agentic Coding | A | Runs well | 93.0 tok/s | 3030 ms | 4K |
| Reasoning | A | Runs well | 93.0 tok/s | 2462 ms | 4K |
| RAG | A | Runs well | 93.0 tok/s | 3787 ms | 4K |
How OLMo 2 32B (32B params) fits at each quantization level on NVIDIA H100 PCIe 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | A73 |
Q3_K_S | 3 | 15.7 GB | Low | A73 |
NVFP4 | 4 |
Copy-paste commands to run OLMo 2 32B on your machine.
Run
lms load OLMo-2-0325-32B-Instruct && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | A | 14.8 tok/s | ||
| 122B | A |
Yes, NVIDIA H100 PCIe 80GB can run OLMo 2 32B with a A grade (Runs well). Expected decode speed: 93.0 tok/s.
OLMo 2 32B (32B parameters) requires approximately 32.6 GB of memory with Q4_K_M quantization.
The recommended quantization for OLMo 2 32B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA H100 PCIe 80GB, OLMo 2 32B achieves approximately 93.0 tokens per second decode speed with a time-to-first-token of 2083ms using Q4_K_M quantization.
For coding workloads, OLMo 2 32B on NVIDIA H100 PCIe 80GB receives a A grade with 93.0 tok/s and 4K context.
On NVIDIA H100 PCIe 80GB, OLMo 2 32B can safely use up to 4K tokens of context. The model's official context limit is 4K, 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-2-32b-on-h100-pcie-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
17.9 GB |
| Medium |
| A74 |
Q4_K_M | 4 | 19.5 GB | Medium | A74 |
Q5_K_M | 5 | 23.0 GB | High | A75 |
Q6_K | 6 | 26.2 GB | High | A75 |
Q8_0 | 8 | 34.2 GB | Very High | A77 |
F16Best for your GPU | 16 | 65.6 GB | Maximum | A80 |
| 44.5 tok/s |
| 35B | S | 213.5 tok/s |
| 35B | S | 232.2 tok/s |
| 119B | A | 47 tok/s |