Solar 7B needs ~10.0 GB VRAM. Tesla P100 16GB has 16.0 GB. With Q4_K_M quantization, expect ~98 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
98.0 tok/s
TTFT
1976 ms
Safe context
8K
Memory
10.0 GB / 16.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 98.0 tok/s | 1078 ms | 8K |
| Coding | A | Runs well | 98.0 tok/s | 1976 ms | 8K |
| Agentic Coding | A | Runs well | 98.0 tok/s | 2873 ms | 8K |
| Reasoning | A | Runs well | 98.0 tok/s | 2335 ms | 8K |
| RAG | A | Runs well | 98.0 tok/s | 3592 ms | 8K |
How Solar 7B (7B params) fits at each quantization level on Tesla P100 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B67 |
Q3_K_S | 3 | 3.4 GB | Low | B68 |
NVFP4 | 4 | 3.9 GB | Medium | B68 |
Q4_K_M | 4 | 4.3 GB | Medium | B69 |
Q5_K_M | 5 | 5.0 GB | High | B69 |
Q6_K | 6 | 5.7 GB | High | A70 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A72 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Solar 7B on your machine.
Run
lms load Solar-7B && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 84.6 tok/s | |
| Qwen 3 14B | 14B | S | 54.6 tok/s | |
| Qwen 3 8B | 8B | S | 95.1 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | S | 51.8 tok/s | |
 GPT-OSS 20B | 21B | A | 46.4 tok/s |
Yes, Tesla P100 16GB can run Solar 7B with a A grade (Runs well). Expected decode speed: 98.0 tok/s.
Solar 7B (7B parameters) requires approximately 10.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Solar 7B is Q4_K_M, which balances quality and memory efficiency.
On Tesla P100 16GB, Solar 7B achieves approximately 98.0 tokens per second decode speed with a time-to-first-token of 1976ms using Q4_K_M quantization.
For coding workloads, Solar 7B on Tesla P100 16GB receives a A grade with 98.0 tok/s and 8K context.
On Tesla P100 16GB, Solar 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, 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/solar-7b-on-tesla-p100-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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