Qwen 3 8B needs ~10.3 GB VRAM. RTX 4000 Ada 20GB has 20.0 GB. With Q4_K_M quantization, expect ~62 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
61.9 tok/s
TTFT
3130 ms
Safe context
87K
Memory
10.3 GB / 20.0 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 | S | Runs well | 61.9 tok/s | 1707 ms | 87K |
| Coding | S | Runs well | 61.9 tok/s | 3130 ms | 87K |
| Agentic Coding | S | Runs well | 61.9 tok/s | 4552 ms | 87K |
| Reasoning | S | Runs well | 61.9 tok/s | 3699 ms | 87K |
| RAG | S | Runs well | 61.9 tok/s | 5691 ms | 87K |
How Qwen 3 8B (8B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | S85 |
Q3_K_S | 3 | 3.9 GB | Low | S86 |
NVFP4 | 4 | 4.5 GB | Medium | S86 |
Q4_K_M | 4 | 4.9 GB | Medium | S87 |
Q5_K_M | 5 | 5.8 GB | High | S87 |
Q6_K | 6 | 6.6 GB | High | S88 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | S90 |
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 |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | A | 23.2 tok/s | |
| Qwen 3.5 27B | 27B | A | 10.4 tok/s | |
| Qwen 3.6 27B | 27B | S | 13 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | A | 24.6 tok/s | |
| Qwen 3.5 9B | 9B | S | 55 tok/s |
Yes, RTX 4000 Ada 20GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 61.9 tok/s.
Qwen 3 8B (8B parameters) requires approximately 10.3 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 RTX 4000 Ada 20GB, Qwen 3 8B achieves approximately 61.9 tokens per second decode speed with a time-to-first-token of 3130ms using Q4_K_M quantization.
For coding workloads, Qwen 3 8B on RTX 4000 Ada 20GB receives a S grade with 61.9 tok/s and 87K context.
On RTX 4000 Ada 20GB, Qwen 3 8B can safely use up to 87K tokens of context. The model's official context limit is 131K, 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/qwen-3-8b-on-rtx-4000-ada-20gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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