OLMo 2 32B needs ~27.5 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~21 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
Tight fit
Decode
20.9 tok/s
TTFT
9267 ms
Safe context
4K
Memory
27.5 GB / 32.0 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 | 20.9 tok/s | 5055 ms | 4K |
| Coding | A | Tight fit | 20.9 tok/s | 9267 ms | 4K |
| Agentic Coding | A | Runs with offload | 20.9 tok/s | 13479 ms | 4K |
| Reasoning | A | Tight fit | 20.9 tok/s | 10952 ms | 4K |
| RAG | A | Runs with offload | 20.9 tok/s | 16849 ms | 4K |
How OLMo 2 32B (32B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | A80 |
Q3_K_S | 3 | 15.7 GB | Low | A82 |
NVFP4 | 4 | 17.9 GB | Medium | A82 |
Q4_K_M | 4 | 19.5 GB | Medium | A81 |
Q5_K_MBest for your GPU | 5 | 23.0 GB | High | A81 |
Q6_K | 6 | 26.2 GB | High | F0 |
Q8_0 | 8 | 34.2 GB | Very High | F0 |
F16 | 16 | 65.6 GB | Maximum | F0 |
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 |
|---|---|---|---|---|
 Qwen 3.6 35B A3B | 35B | S | 48 tok/s | |
| Qwen 3.5 35B A3B | 35B | S | 52.2 tok/s | |
 Kimi Linear 48B A3B | 48B | B | 8.6 tok/s |
Yes, Radeon AI PRO R9700 32GB can run OLMo 2 32B with a A grade (Tight fit). Expected decode speed: 20.9 tok/s.
OLMo 2 32B (32B parameters) requires approximately 27.5 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 Radeon AI PRO R9700 32GB, OLMo 2 32B achieves approximately 20.9 tokens per second decode speed with a time-to-first-token of 9267ms using Q4_K_M quantization.
For coding workloads, OLMo 2 32B on Radeon AI PRO R9700 32GB receives a A grade with 20.9 tok/s and 4K context.
On Radeon AI PRO R9700 32GB, 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-radeon-ai-pro-r9700-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: