C89.7 tok/s decode
~$249 MSRP
Can it run?
Too heavy
Using Q4_K_M in Ollama
Fit status
Too heavy
Decode
56.7 tok/s
TTFT
3417 ms
Safe context
13K
Memory
4.8 GB / 4.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 61.4 tok/s | 4588 ms | 24K |
| Chat | F | Too heavy | 61.4 tok/s | 1721 ms | 7K |
| Coding | F | Too heavy | 56.7 tok/s | 3417 ms | 13K |
| RAG | F | Too heavy | 61.4 tok/s | 5735 ms | 24K |
| Reasoning | F | Too heavy | 61.4 tok/s | 3728 ms | 13K |
How gemma 3 4b it (4B params) fits at each quantization level on RTX 3050 Ti Laptop 4GB (4.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_KBest for your GPU | 2 | 1.6 GB | Low | D38 |
Q3_K_S | 3 | 2.0 GB | Low | C40 |
Upgrade options
~$249 MSRP
~$269 MSRP
~$399 MSRP
| 4 |
2.2 GB |
| Medium |
| C41 |
Q4_K_M | 4 | 2.4 GB | Medium | C42 |
Q5_K_M | 5 | 2.9 GB | High | C44 |
Q6_K | 6 | 3.3 GB | High | C44 |
Q8_0 | 8 | 4.3 GB | Very High | F0 |
F16 | 16 | 8.2 GB | Maximum | F0 |