Gemma 2 27B needs ~31.8 GB VRAM. Radeon Pro W6800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~13 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 with offload
Decode
13.9 tok/s
TTFT
13975 ms
Safe context
8K
Memory
31.8 GB / 32.0 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 | A | Runs well | 13.9 tok/s | 7623 ms | 8K |
| Coding | B | Runs with offload | 13.2 tok/s | 14674 ms | 8K |
| Agentic Coding | F | Too heavy | 5.6 tok/s | 50559 ms | 8K |
| Reasoning | B | Runs with offload | 13.9 tok/s | 16516 ms | 8K |
| RAG | F | Too heavy | 5.6 tok/s | 63199 ms | 8K |
How Gemma 2 27B (27B params) fits at each quantization level on Radeon Pro W6800 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | B66 |
Q3_K_S | 3 | 13.2 GB | Low | B67 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 2 27B on your machine.
Run
ollama run gemma2:27bUpgrade options
Raises estimated decode speed by about 67%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 67%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 217%.
Adds memory headroom for longer context windows and future model growth.
~$10,000 MSRP
Yes, Radeon Pro W6800 32GB can run Gemma 2 27B with a B grade (Runs with offload). Expected decode speed: 13.2 tok/s.
Gemma 2 27B (27B parameters) requires approximately 31.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 2 27B is Q4_K_M, which balances quality and memory efficiency.
On Radeon Pro W6800 32GB, Gemma 2 27B achieves approximately 13.2 tokens per second decode speed with a time-to-first-token of 14674ms using Q4_K_M quantization.
For coding workloads, Gemma 2 27B on Radeon Pro W6800 32GB receives a B grade with 13.2 tok/s and 8K context.
On Radeon Pro W6800 32GB, Gemma 2 27B 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-2-27b-on-radeon-pro-w6800-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| B68 |
Q4_K_M | 4 | 16.5 GB | Medium | B69 |
Q5_K_M | 5 | 19.4 GB | High | B69 |
Q6_KBest for your GPU | 6 | 22.1 GB | High | B68 |
Q8_0 | 8 | 28.9 GB | Very High | F0 |
F16 | 16 | 55.4 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.