solar finalised finetuned Model 10.7B i1 needs ~10.6 GB VRAM. RTX 4070 Ti Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~82 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
82.4 tok/s
TTFT
2350 ms
Safe context
85K
Memory
10.6 GB / 16.0 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 | 82.4 tok/s | 1282 ms | 85K |
| Coding | B | Runs well | 82.4 tok/s | 2350 ms | 85K |
| Agentic Coding | B | Runs well | 82.4 tok/s | 3419 ms | 85K |
| Reasoning | B | Runs well | 82.4 tok/s | 2778 ms | 85K |
| RAG | B | Runs well | 82.4 tok/s | 4274 ms | 85K |
How solar finalised finetuned Model 10.7B i1 (10.699999809265137B params) fits at each quantization level on RTX 4070 Ti Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C48 |
Q3_K_S | 3 | 5.2 GB | Low | C49 |
NVFP4 | 4 |
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 startYes, RTX 4070 Ti Super 16GB can run solar finalised finetuned Model 10.7B i1 with a B grade (Runs well). Expected decode speed: 82.4 tok/s.
solar finalised finetuned Model 10.7B i1 (10.699999809265137B parameters) requires approximately 10.6 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 4070 Ti Super 16GB, solar finalised finetuned Model 10.7B i1 achieves approximately 82.4 tokens per second decode speed with a time-to-first-token of 2350ms using Q4_K_M quantization.
For coding workloads, solar finalised finetuned Model 10.7B i1 on RTX 4070 Ti Super 16GB receives a B grade with 82.4 tok/s and 85K context.
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-4070-ti-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
6.0 GB |
| Medium |
| C49 |
Q4_K_M | 4 | 6.5 GB | Medium | C50 |
Q5_K_M | 5 | 7.7 GB | High | C51 |
Q6_K | 6 | 8.8 GB | High | C51 |
Q8_0Best for your GPU | 8 | 11.4 GB | Very High | C50 |
F16 | 16 | 21.9 GB | Maximum | F0 |
On RTX 4070 Ti Super 16GB, solar finalised finetuned Model 10.7B i1 can safely use up to 85K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.