solar finalised finetuned Model 10.7B i1 needs ~15.4 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~72 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
71.7 tok/s
TTFT
2700 ms
Safe context
636K
Memory
15.4 GB / 64.0 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 | 71.7 tok/s | 1473 ms | 636K |
| Coding | C | Runs well | 71.7 tok/s | 2700 ms | 636K |
| Agentic Coding | C | Runs well | 71.7 tok/s | 3927 ms | 636K |
| Reasoning | C | Runs well | 71.7 tok/s | 3191 ms | 636K |
| RAG | C | Runs well | 71.7 tok/s | 4909 ms | 636K |
How solar finalised finetuned Model 10.7B i1 (10.699999809265137B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C40 |
Q3_K_S | 3 | 5.2 GB | Low | C40 |
NVFP4 | 4 | 6.0 GB | Medium | C40 |
Q4_K_M | 4 | 6.5 GB | Medium | C40 |
Q5_K_M | 5 | 7.7 GB | High | C40 |
Q6_K | 6 | 8.8 GB | High | C41 |
Q8_0 | 8 | 11.4 GB | Very High | C41 |
F16Best for your GPU | 16 | 21.9 GB | Maximum | C43 |
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 startOpciones de mejora
NVIDIA A100 80GBOpción económicaSube la velocidad estimada de decodificación alrededor de un 109%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$15,000 MSRP
NVIDIA A800 80GBMejor relación calidad-precioSube la velocidad estimada de decodificación alrededor de un 109%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$15,000 MSRP
NVIDIA H800 80GBMejora NVIDIASube la velocidad estimada de decodificación alrededor de un 109%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
Yes, NVIDIA A16 64GB can run solar finalised finetuned Model 10.7B i1 with a C grade (Runs well). Expected decode speed: 71.7 tok/s.
solar finalised finetuned Model 10.7B i1 (10.699999809265137B parameters) requires approximately 15.4 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 NVIDIA A16 64GB, solar finalised finetuned Model 10.7B i1 achieves approximately 71.7 tokens per second decode speed with a time-to-first-token of 2700ms using Q4_K_M quantization.
For coding workloads, solar finalised finetuned Model 10.7B i1 on NVIDIA A16 64GB receives a C grade with 71.7 tok/s and 636K context.
On NVIDIA A16 64GB, solar finalised finetuned Model 10.7B i1 can safely use up to 636K 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.
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