SOLAR 10.7B v1.0 needs ~9.5 GB VRAM. RX 9060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~15 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
1.5 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~1 GB host RAM)
Decode
14.6 tok/s
TTFT
13277 ms
Safe context
4K
Memory
9.5 GB / 8.0 GB
Offload
20%
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 20% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 1.0 GB of extra host RAM just for the offloaded portion, before OS and other tools.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | D | Very compromised (needs ~0.6 GB host RAM) | 16.8 tok/s | 6271 ms | 4K |
| Coding | D | Very compromised (needs ~1 GB host RAM) | 14.6 tok/s | 13277 ms | 4K |
| Agentic Coding | F | Too heavy | 11.2 tok/s | 25082 ms | 4K |
| Reasoning | D | Very compromised (needs ~1 GB host RAM) | 14.6 tok/s | 15691 ms | 4K |
| RAG | F | Too heavy | 11.2 tok/s | 31353 ms | 4K |
How SOLAR 10.7B v1.0 (10.699999809265137B params) fits at each quantization level on RX 9060 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C53 |
Q3_K_SBest for your GPU | 3 | 5.2 GB | Low | C52 |
NVFP4 | 4 | 6.0 GB | Medium | F0 |
Q4_K_M | 4 | 6.5 GB | Medium | F0 |
Q5_K_M | 5 | 7.7 GB | High | F0 |
Q6_K | 6 | 8.8 GB | High | F0 |
Q8_0 | 8 | 11.4 GB | Very High | F0 |
F16 | 16 | 21.9 GB | Maximum | F0 |
Copy-paste commands to run SOLAR 10.7B v1.0 on your machine.
Run
lms load hf-mradermacher--solar-10-7b-v1-0-gguf && lms server startUpgrade options
Removes host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 75%.
~$329 MSRP
Removes host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 112%.
~$349 MSRP
Removes host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 172%.
~$449 MSRP
Yes, RX 9060 8GB can run SOLAR 10.7B v1.0 with a D grade (Very compromised (needs ~1 GB host RAM)). Expected decode speed: 14.6 tok/s.
SOLAR 10.7B v1.0 (10.699999809265137B parameters) requires approximately 9.5 GB of memory with Q4_K_M quantization.
The recommended quantization for SOLAR 10.7B v1.0 is Q4_K_M, which balances quality and memory efficiency.
On RX 9060 8GB, SOLAR 10.7B v1.0 achieves approximately 14.6 tokens per second decode speed with a time-to-first-token of 13277ms using Q4_K_M quantization.
For coding workloads, SOLAR 10.7B v1.0 on RX 9060 8GB receives a D grade with 14.6 tok/s and 4K context.
On RX 9060 8GB, SOLAR 10.7B v1.0 can safely use up to 4K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
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