RTX 5060 Ti 16GBBudget pick16 GB VRAM (+4)448 GB/s (+16)
C
Adds memory headroom for longer context windows and future model growth.41.3 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$449 MSRP
solar finalised finetuned Model 10.7B i1 needs ~9.9 GB VRAM. RTX 4080 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
Tight fit
Decode
54.2 tok/s
TTFT
3572 ms
Safe context
43K
Memory
9.9 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 | C | Runs well | 54.2 tok/s | 1948 ms | 43K |
| Coding | C | Tight fit | 54.2 tok/s | 3572 ms | 43K |
| Agentic Coding | C | Tight fit | 54.2 tok/s | 5195 ms | 43K |
| Reasoning | C | Tight fit | 54.2 tok/s | 4221 ms | 43K |
| RAG | C | Tight fit | 54.2 tok/s | 6494 ms | 43K |
How solar finalised finetuned Model 10.7B i1 (10.699999809265137B params) fits at each quantization level on RTX 4080 Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C51 |
Q3_K_S | 3 | 5.2 GB | Low | C52 |
NVFP4 | 4 | 6.0 GB | Medium | C52 |
Q4_K_M | 4 | 6.5 GB | Medium | C52 |
Q5_K_M | 5 | 7.7 GB | High | C51 |
Q6_KBest for your GPU | 6 | 8.8 GB | High | C51 |
Q8_0 | 8 | 11.4 GB | Very High | F0 |
F16 | 16 | 21.9 GB | Maximum | F0 |
Copy-paste commands to run solar finalised finetuned Model 10.7B i1 on your machine.
Run
lms load hf-mradermacher--solar-finalised-finetuned-model-10-7b-i1-gguf && lms server startUpgrade options
RTX 5060 Ti 16GBBudget pickAdds memory headroom for longer context windows and future model growth.
~$449 MSRP
RTX 4060 Ti 16GBBest valueAdds memory headroom for longer context windows and future model growth.
~$499 MSRP
RTX 5070 Ti 16GBNVIDIA upgradeRaises estimated decode speed by about 57%.
Adds memory headroom for longer context windows and future model growth.
~$749 MSRP
Yes, RTX 4080 Laptop 12GB can run solar finalised finetuned Model 10.7B i1 with a C grade (Tight fit). Expected decode speed: 54.2 tok/s.
solar finalised finetuned Model 10.7B i1 (10.699999809265137B parameters) requires approximately 9.9 GB of memory with Q4_K_M quantization.
The recommended quantization for solar finalised finetuned Model 10.7B i1 is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Laptop 12GB, solar finalised finetuned Model 10.7B i1 achieves approximately 54.2 tokens per second decode speed with a time-to-first-token of 3572ms using Q4_K_M quantization.
For coding workloads, solar finalised finetuned Model 10.7B i1 on RTX 4080 Laptop 12GB receives a C grade with 54.2 tok/s and 43K context.
On RTX 4080 Laptop 12GB, solar finalised finetuned Model 10.7B i1 can safely use up to 43K tokens of context. The model's official context limit is —, 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/hf-mradermacher--solar-finalised-finetuned-model-10-7b-i1-gguf-on-rtx-4080-laptop-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: