Raises estimated decode speed by about 41%.
Adds memory headroom for longer context windows and future model growth.
~$899 MSRP
Gemma 2 9B needs ~13.1 GB VRAM. Radeon PRO W7700 16GB has 16.0 GB. With Q4_K_M quantization, expect ~49 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
49.3 tok/s
TTFT
3930 ms
Safe context
8K
Memory
13.1 GB / 16.0 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 | Runs well | 49.3 tok/s | 2144 ms | 8K |
| Coding | B | Runs well | 49.3 tok/s | 3930 ms | 8K |
| Agentic Coding | C | Very compromised (needs ~0.7 GB host RAM) | 28.0 tok/s | 10048 ms | 8K |
| Reasoning | B | Runs well | 49.3 tok/s | 4645 ms | 8K |
| RAG | C | Very compromised (needs ~0.7 GB host RAM) | 28.0 tok/s | 12560 ms |
How Gemma 2 9B (9B params) fits at each quantization level on Radeon PRO W7700 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B62 |
Q3_K_S | 3 | 4.4 GB | Low | B63 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 2 9B on your machine.
Run
ollama run gemma2Upgrade options
Raises estimated decode speed by about 41%.
Adds memory headroom for longer context windows and future model growth.
~$899 MSRP
Raises estimated decode speed by about 47%.
Adds memory headroom for longer context windows and future model growth.
~$2,000 MSRP
Yes, Radeon PRO W7700 16GB can run Gemma 2 9B with a B grade (Runs well). Expected decode speed: 49.3 tok/s.
Gemma 2 9B (9B parameters) requires approximately 13.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 2 9B is Q4_K_M, which balances quality and memory efficiency.
On Radeon PRO W7700 16GB, Gemma 2 9B achieves approximately 49.3 tokens per second decode speed with a time-to-first-token of 3930ms using Q4_K_M quantization.
For coding workloads, Gemma 2 9B on Radeon PRO W7700 16GB receives a B grade with 49.3 tok/s and 8K context.
On Radeon PRO W7700 16GB, Gemma 2 9B can safely use up to 8K tokens of context. The model's official context limit is 8K, 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/gemma-2-9b-on-radeon-pro-w7700-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 8K |
5.0 GB |
| Medium |
| B63 |
Q4_K_M | 4 | 5.5 GB | Medium | B64 |
Q5_K_M | 5 | 6.5 GB | High | B65 |
Q6_K | 6 | 7.4 GB | High | B66 |
Q8_0Best for your GPU | 8 | 9.6 GB | Very High | B66 |
F16 | 16 | 18.5 GB | Maximum | F0 |