Qwen 3 30B A3B needs ~23.7 GB VRAM. RTX 5090 Laptop 24GB has 24.0 GB. With Q4_K_M quantization, expect ~114 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
113.8 tok/s
TTFT
1701 ms
Safe context
20K
Memory
23.7 GB / 24.0 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 | S | Runs with offload | 113.8 tok/s | 928 ms | 20K |
| Coding | S | Runs with offload | 113.8 tok/s | 1701 ms | 20K |
| Agentic Coding | S | Runs with offload (needs ~0.8 GB host RAM) | 77.4 tok/s | 3636 ms | 20K |
| Reasoning | S | Runs with offload | 104.7 tok/s | 2186 ms | 20K |
| RAG | S | Runs with offload (needs ~0.8 GB host RAM) | 77.4 tok/s | 4545 ms |
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on RTX 5090 Laptop 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | S91 |
Q3_K_S | 3 | 14.9 GB | Low | S90 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 35B | A | 63.8 tok/s | ||
| 32B | A | 24.5 tok/s |
Yes, RTX 5090 Laptop 24GB can run Qwen 3 30B A3B with a S grade (Runs with offload). Expected decode speed: 113.8 tok/s.
Qwen 3 30B A3B (30.5B parameters) requires approximately 23.7 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 5090 Laptop 24GB, Qwen 3 30B A3B achieves approximately 113.8 tokens per second decode speed with a time-to-first-token of 1701ms using Q4_K_M quantization.
For coding workloads, Qwen 3 30B A3B on RTX 5090 Laptop 24GB receives a S grade with 113.8 tok/s and 20K context.
On RTX 5090 Laptop 24GB, Qwen 3 30B A3B can safely use up to 20K 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-3-30b-a3b-on-rtx-5090-laptop-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 20K |
17.1 GB |
| Medium |
| S90 |
Q4_K_MBest for your GPU | 4 | 18.6 GB | Medium | S90 |
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 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.