Qwen 3 30B A3B needs ~22.1 GB but RTX 5060 Ti 8GB only has 8.0 GB. Try a smaller quantization or lighter model.
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
14.1 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
6.3 tok/s
TTFT
30730 ms
Safe context
4K
Memory
22.1 GB / 8.0 GB
Offload
60%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 22.1 GB, but this setup only exposes 8.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 5.8 tok/s | 18228 ms | 4K |
| Coding | F | Too heavy | 5.8 tok/s | 33419 ms | 4K |
| Agentic Coding | F | Too heavy | 5.8 tok/s | 48609 ms | 4K |
| Reasoning | F | Too heavy | 5.8 tok/s | 39495 ms | 4K |
| RAG | F | Too heavy | 5.8 tok/s | 60761 ms | 4K |
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on RTX 5060 Ti 8GB (8.0 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 |
Opciones de mejora
RTX 4000 Ada 20GBMejor relación calidad-precioHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Sube la velocidad estimada de decodificación alrededor de un 268%.
~$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
No, Qwen 3 30B A3B requires more memory than RTX 5060 Ti 8GB provides.
Qwen 3 30B A3B (30.5B parameters) requires approximately 22.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 3 30B A3B is Q4_K_M, which balances quality and memory efficiency.
On RTX 5060 Ti 8GB, Qwen 3 30B A3B achieves approximately 5.8 tokens per second decode speed with a time-to-first-token of 33419ms using Q4_K_M quantization.
For coding workloads, Qwen 3 30B A3B on RTX 5060 Ti 8GB receives a F grade with 5.8 tok/s and 4K context.
On RTX 5060 Ti 8GB, Qwen 3 30B A3B can safely use up to 4K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-30b-a3b-on-rtx-5060-ti-8gb" 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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