Qwen 3 8B needs ~9.5 GB VRAM. RTX 3500 Ada Laptop 12GB has 12.0 GB. With Q4_K_M quantization, expect ~54 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
54.0 tok/s
TTFT
3583 ms
Safe context
34K
Memory
9.5 GB / 12.0 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 | 54.0 tok/s | 1954 ms | 34K |
| Coding | S | Runs well | 54.0 tok/s | 3583 ms | 34K |
| Agentic Coding | S | Runs with offload | 54.0 tok/s | 5212 ms | 34K |
| Reasoning | S | Runs well | 54.0 tok/s | 4235 ms | 34K |
| RAG | S | Runs with offload | 54.0 tok/s | 6515 ms | 34K |
Inference speed
Estimated decode speed (tokens/sec) for Qwen 3 8B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~112 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 112.0 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 112.0 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 112.0 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 112.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 102.2 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 96.9 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 83.3 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 82.6 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 82.6 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 52.9 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 52.3 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 48.5 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 42.6 | Fits |
| RTX 4060 8GB | 8 GB | Q4_K_M | 25.1 | Heavy offload |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How Qwen 3 8B (8B params) fits at each quantization level on RTX 3500 Ada Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | S89 |
Q3_K_S | 3 | 3.9 GB | Low | S90 |
NVFP4 | 4 | 4.5 GB | Medium | S91 |
Q4_K_M | 4 | 4.9 GB | Medium | S92 |
Q5_K_M | 5 | 5.8 GB | High | S92 |
Q6_K | 6 | 6.6 GB | High | S92 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | S91 |
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 |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 48 tok/s | |
| Qwen 3 14B | 14B | A | 18.5 tok/s |
Yes, RTX 3500 Ada Laptop 12GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 54.0 tok/s.
Qwen 3 8B (8B parameters) requires approximately 9.5 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 3500 Ada Laptop 12GB, Qwen 3 8B achieves approximately 54.0 tokens per second decode speed with a time-to-first-token of 3583ms using Q4_K_M quantization.
For coding workloads, Qwen 3 8B on RTX 3500 Ada Laptop 12GB receives a S grade with 54.0 tok/s and 34K context.
On RTX 3500 Ada Laptop 12GB, Qwen 3 8B can safely use up to 34K 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.
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