Qwen 3 30B A3B needs ~16.2 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q2_K quantization, expect ~90 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
6.9 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
32.7 tok/s
TTFT
5928 ms
Safe context
4K
Memory
22.9 GB / 16.0 GB
Offload
30%
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 | F | Too heavy | 35.0 tok/s | 3019 ms | 4K |
| Coding | F | Too heavy | 32.7 tok/s | 5928 ms | 4K |
| Agentic Coding | F | Too heavy | 28.7 tok/s | 9826 ms | 4K |
| Reasoning | F | Too heavy | 32.7 tok/s | 7005 ms | 4K |
| RAG | F | Too heavy | 28.7 tok/s | 12282 ms | 4K |
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | F0 |
Q3_K_S | 3 | 14.9 GB | Low | F0 |
NVFP4 | 4 | 17.1 GB | Medium | F0 |
Q4_K_M | 4 | 18.6 GB | Medium | F0 |
Q5_K_M | 5 | 22.0 GB | High | F0 |
Q6_K | 6 | 25.0 GB | High | F0 |
Q8_0 | 8 | 32.6 GB | Very High | F0 |
F16 | 16 | 62.5 GB | Maximum | F0 |
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3bOpciones de mejora
RTX 4000 Ada 20GBMejor relación calidad-precioHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$1,250 MSRP
RTX 3090 24GBOpción económicaHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$1,499 MSRP
RTX 4090 24GBMejora NVIDIAHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$1,599 MSRP
Yes, RTX 4080 Super 16GB can run Qwen 3 30B A3B at Q2_K quantization (Runs with offload (needs ~0.1 GB host RAM)). The recommended Q4_K_M requires 22.9 GB which exceeds available memory, but at Q2_K it needs only 16.2 GB. Expected decode speed: 90.2 tok/s.
Qwen 3 30B A3B (30.5B parameters) requires approximately 22.9 GB at Q4_K_M quantization. On RTX 4080 Super 16GB, it fits at Q2_K using 16.2 GB.
The recommended quantization is Q4_K_M, but on RTX 4080 Super 16GB the best fitting quantization is Q2_K, which uses 16.2 GB.
On RTX 4080 Super 16GB, Qwen 3 30B A3B achieves approximately 90.2 tokens per second decode speed with a time-to-first-token of 2146ms using Q2_K quantization.
For coding workloads, Qwen 3 30B A3B on RTX 4080 Super 16GB receives a F grade with 32.7 tok/s and 4K context.
On RTX 4080 Super 16GB, Qwen 3 30B A3B can safely use up to 14K tokens of context at Q2_K quantization. The model's official context limit is 131K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-30b-a3b-on-rtx-4080-super-16gb" 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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