Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 44%.
~$249 MSRP
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VOOZH | about |
Solar 7B needs ~9.0 GB but RTX 2060 6GB only has 6.0 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
3.0 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
14.4 tok/s
TTFT
13409 ms
Safe context
4K
Memory
9.0 GB / 6.0 GB
Offload
30%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 9.0 GB, but this setup only exposes 6.0 GB of usable VRAM.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
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 | 19.8 tok/s | 5323 ms | 4K |
| Coding | F | Too heavy | 13.4 tok/s | 14415 ms | 4K |
| Agentic Coding | F | Too heavy | 7.2 tok/s | 38932 ms | 4K |
| Reasoning | F | Too heavy | 13.4 tok/s | 17036 ms | 4K |
| RAG | F | Too heavy | 7.2 tok/s | 48665 ms | 4K |
How Solar 7B (7B params) fits at each quantization level on RTX 2060 6GB (6.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A75 |
Q3_K_SBest for your GPU | 3 | 3.4 GB | Low | A74 |
Upgrade options
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 44%.
~$249 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 175%.
~$299 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$329 MSRP
| 4 |
3.9 GB |
| Medium |
| F0 |
Q4_K_M | 4 | 4.3 GB | Medium | F0 |
Q5_K_M | 5 | 5.0 GB | High | F0 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |