RX 7600 XT 16GBBudget pick
16 GB VRAM (+8)288 GB/s (+64)
C
Raises estimated decode speed by about 80%.30.4 tok/s decode
Raises estimated decode speed by about 80%.
Adds memory headroom for longer context windows and future model growth.
~$329 MSRP
Yi 1.5 9B Chat needs ~8.2 GB VRAM. Radeon Pro W7500 8GB has 8.0 GB. With Q4_K_M quantization, expect ~17 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
0.2 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~0.2 GB host RAM)
Decode
16.9 tok/s
TTFT
11425 ms
Safe context
12K
Memory
8.2 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs with offload | 24.1 tok/s | 4387 ms | 12K |
| Coding | C | Runs with offload | 16.9 tok/s | 11425 ms | 12K |
| Agentic Coding | D | Very compromised | 13.2 tok/s | 21411 ms | 12K |
| Reasoning | C | Runs with offload | 16.9 tok/s | 13502 ms | 12K |
| RAG | D | Very compromised | 13.2 tok/s | 26764 ms | 12K |
How Yi 1.5 9B Chat (9B params) fits at each quantization level on Radeon Pro W7500 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C53 |
Q3_K_S | 3 | 4.4 GB | Low | C53 |
NVFP4Best for your GPU |
Copy-paste commands to run Yi 1.5 9B Chat on your machine.
Run
lms load hf-bartowski--yi-1-5-9b-chat-gguf && lms server startUpgrade options
Raises estimated decode speed by about 80%.
Adds memory headroom for longer context windows and future model growth.
~$329 MSRP
Raises estimated decode speed by about 117%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
Raises estimated decode speed by about 179%.
Adds memory headroom for longer context windows and future model growth.
~$449 MSRP
Yes, Radeon Pro W7500 8GB can run Yi 1.5 9B Chat with a C grade (Runs with offload). Expected decode speed: 16.9 tok/s.
Yi 1.5 9B Chat (9B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi 1.5 9B Chat is Q4_K_M, which balances quality and memory efficiency.
On Radeon Pro W7500 8GB, Yi 1.5 9B Chat achieves approximately 16.9 tokens per second decode speed with a time-to-first-token of 11425ms using Q4_K_M quantization.
For coding workloads, Yi 1.5 9B Chat on Radeon Pro W7500 8GB receives a C grade with 16.9 tok/s and 12K context.
On Radeon Pro W7500 8GB, Yi 1.5 9B Chat can safely use up to 12K tokens of context. The model's official context limit is —, 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/hf-bartowski--yi-1-5-9b-chat-gguf-on-radeon-pro-w7500-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 4 |
5.0 GB |
| Medium |
| C53 |
Q4_K_M | 4 | 5.5 GB | Medium | F0 |
Q5_K_M | 5 | 6.5 GB | High | F0 |
Q6_K | 6 | 7.4 GB | High | F0 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.