Qwen 3 8B needs ~8.8 GB VRAM. RX 6650 XT 8GB has 8.0 GB. With Q4_K_M quantization, expect ~19 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
0.8 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~0.4 GB host RAM)
Decode
19.4 tok/s
TTFT
9975 ms
Safe context
10K
Memory
8.8 GB / 8.0 GB
Offload
10%
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
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.
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 0.4 GB of extra host RAM just for the offloaded portion, before OS and other tools.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload | 31.5 tok/s | 3357 ms | 10K |
| Coding | A | Very compromised (needs ~0.4 GB host RAM) | 19.4 tok/s | 9975 ms | 10K |
| Agentic Coding | F | Too heavy | 12.1 tok/s | 23220 ms | 10K |
| Reasoning | A | Very compromised (needs ~0.4 GB host RAM) | 19.4 tok/s | 11788 ms | 10K |
| RAG | F | Too heavy | 12.1 tok/s | 29025 ms | 10K |
How Qwen 3 8B (8B params) fits at each quantization level on RX 6650 XT 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | S94 |
Q3_K_S | 3 | 3.9 GB | Low | S93 |
NVFP4 | 4 | 4.5 GB | Medium | S93 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | S93 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run Qwen 3 8B on your machine.
Run
ollama run qwen3:8bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | A | 15 tok/s |
Yes, RX 6650 XT 8GB can run Qwen 3 8B with a A grade (Very compromised (needs ~0.4 GB host RAM)). Expected decode speed: 19.4 tok/s.
Qwen 3 8B (8B parameters) requires approximately 8.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 3 8B is Q4_K_M, which balances quality and memory efficiency.
On RX 6650 XT 8GB, Qwen 3 8B achieves approximately 19.4 tokens per second decode speed with a time-to-first-token of 9975ms using Q4_K_M quantization.
For coding workloads, Qwen 3 8B on RX 6650 XT 8GB receives a A grade with 19.4 tok/s and 10K context.
On RX 6650 XT 8GB, Qwen 3 8B can safely use up to 10K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-8b-on-rx-6650-xt-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: