StarCoder 7B needs ~14.4 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
Tight fit
Decode
98.0 tok/s
TTFT
1976 ms
Safe context
8K
Memory
14.4 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 | Tight fit | 98.0 tok/s | 1976 ms | 8K |
| Agentic Coding | F | Too heavy | 37.7 tok/s | 7467 ms | 8K |
| Reasoning | A | Tight fit | 98.0 tok/s | 2335 ms | 8K |
| RAG | F | Too heavy | 37.7 tok/s | 9334 ms | 8K |
How StarCoder 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 | A70 |
Q3_K_S | 3 | 3.4 GB | Low | A71 |
NVFP4 | 4 |
Copy-paste commands to run StarCoder 7B on your machine.
Run
lms load starcoder-7b && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 84.6 tok/s | ||
| 14B | S | 54.6 tok/s |
Yes, Tesla P100 16GB can run StarCoder 7B with a A grade (Tight fit). Expected decode speed: 98.0 tok/s.
StarCoder 7B (7B parameters) requires approximately 14.4 GB of memory with Q4_K_M quantization.
The recommended quantization for StarCoder 7B is Q4_K_M, which balances quality and memory efficiency.
On Tesla P100 16GB, StarCoder 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, StarCoder 7B on Tesla P100 16GB receives a A grade with 98.0 tok/s and 8K context.
On Tesla P100 16GB, StarCoder 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/starcoder-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>
Preview:
3.9 GB |
| Medium |
| A71 |
Q4_K_M | 4 | 4.3 GB | Medium | A71 |
Q5_K_M | 5 | 5.0 GB | High | A72 |
Q6_K | 6 | 5.7 GB | High | A73 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A75 |
F16 | 16 | 14.3 GB | Maximum | F0 |
| 8B | S | 95.1 tok/s |
| 14.7B | S | 51.8 tok/s |
| 21B | A | 46.4 tok/s |