Adds memory headroom for longer context windows and future model growth.
~$4,650 MSRP
Yi 1.5 34B needs ~28.8 GB VRAM. RTX PRO 4500 Blackwell 32GB has 32.0 GB. With Q4_K_M quantization, expect ~36 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
39.4 tok/s
TTFT
4914 ms
Safe context
4K
Memory
28.8 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 | B | Tight fit | 39.4 tok/s | 2680 ms | 4K |
| Coding | B | Tight fit | 36.3 tok/s | 5335 ms | 4K |
| Agentic Coding | B | Runs with offload (needs ~0.3 GB host RAM) | 29.3 tok/s | 9625 ms | 4K |
| Reasoning | B | Tight fit | 39.4 tok/s | 5807 ms | 4K |
| RAG | B | Runs with offload (needs ~0.3 GB host RAM) | 29.3 tok/s | 12031 ms |
How Yi 1.5 34B (34B params) fits at each quantization level on RTX PRO 4500 Blackwell 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.3 GB | Low | B61 |
Q3_K_S | 3 | 16.7 GB | Low | B62 |
NVFP4 | 4 |
Copy-paste commands to run Yi 1.5 34B on your machine.
Run
lms load Yi-1.5-34B-Chat && lms server startUpgrade options
Adds memory headroom for longer context windows and future model growth.
~$4,650 MSRP
Raises estimated decode speed by about 50%.
Adds memory headroom for longer context windows and future model growth.
~$4,999 MSRP
Adds memory headroom for longer context windows and future model growth.
~$5,500 MSRP
Yes, RTX PRO 4500 Blackwell 32GB can run Yi 1.5 34B with a B grade (Tight fit). Expected decode speed: 36.3 tok/s.
Yi 1.5 34B (34B parameters) requires approximately 28.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi 1.5 34B is Q4_K_M, which balances quality and memory efficiency.
On RTX PRO 4500 Blackwell 32GB, Yi 1.5 34B achieves approximately 36.3 tokens per second decode speed with a time-to-first-token of 5335ms using Q4_K_M quantization.
For coding workloads, Yi 1.5 34B on RTX PRO 4500 Blackwell 32GB receives a B grade with 36.3 tok/s and 4K context.
On RTX PRO 4500 Blackwell 32GB, Yi 1.5 34B 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/yi-1.5-34b-on-rtx-pro-4500-blackwell-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 4K |
19.0 GB |
| Medium |
| B62 |
Q4_K_M | 4 | 20.7 GB | Medium | B62 |
Q5_K_MBest for your GPU | 5 | 24.5 GB | High | B61 |
Q6_K | 6 | 27.9 GB | High | F0 |
Q8_0 | 8 | 36.4 GB | Very High | F0 |
F16 | 16 | 69.7 GB | Maximum | F0 |