Qwen 3 30B A3B needs ~23.4 GB VRAM. RTX 4090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~83 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
83.4 tok/s
TTFT
2321 ms
Safe context
23K
Memory
23.4 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 | Tight fit | 83.4 tok/s | 1266 ms | 23K |
| Coding | S | Runs with offload | 83.4 tok/s | 2321 ms | 23K |
| Agentic Coding | S | Runs with offload (needs ~0.6 GB host RAM) | 58.2 tok/s | 4838 ms | 23K |
| Reasoning | S | Runs with offload | 83.4 tok/s | 2743 ms | 23K |
| RAG | S | Runs with offload (needs ~0.6 GB host RAM) | 58.2 tok/s | 6047 ms | 23K |
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on RTX 4090 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 | 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 |
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.6 35B A3B | 35B | A | 53.4 tok/s | |
| Qwen 3.5 35B A3B | 35B | A | 71.1 tok/s | |
| Qwen 3 32B | 32B | A | 13.1 tok/s |
Yes, RTX 4090 24GB can run Qwen 3 30B A3B with a S grade (Runs with offload). Expected decode speed: 83.4 tok/s.
Qwen 3 30B A3B (30.5B parameters) requires approximately 23.4 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 4090 24GB, Qwen 3 30B A3B achieves approximately 83.4 tokens per second decode speed with a time-to-first-token of 2321ms using Q4_K_M quantization.
For coding workloads, Qwen 3 30B A3B on RTX 4090 24GB receives a S grade with 83.4 tok/s and 23K context.
On RTX 4090 24GB, Qwen 3 30B A3B can safely use up to 23K tokens of context. 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-4090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: