starcoder2 15b instruct v0.1 needs ~14.5 GB VRAM. Quadro RTX 6000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~51 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
50.7 tok/s
TTFT
3820 ms
Safe context
102K
Memory
14.5 GB / 24.0 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 | C | Runs well | 50.7 tok/s | 2084 ms | 102K |
| Coding | C | Runs well | 50.7 tok/s | 3820 ms | 102K |
| Agentic Coding | C | Runs well | 50.7 tok/s | 5557 ms | 102K |
| Reasoning | C | Runs well | 50.7 tok/s | 4515 ms | 102K |
| RAG | C | Runs well | 50.7 tok/s | 6946 ms | 102K |
How starcoder2 15b instruct v0.1 (15B params) fits at each quantization level on Quadro RTX 6000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C46 |
Q3_K_S | 3 | 7.4 GB | Low | C47 |
NVFP4 | 4 |
Copy-paste commands to run starcoder2 15b instruct v0.1 on your machine.
Run
lms load hf-bartowski--starcoder2-15b-instruct-v0-1-gguf && lms server startYes, Quadro RTX 6000 24GB can run starcoder2 15b instruct v0.1 with a C grade (Runs well). Expected decode speed: 50.7 tok/s.
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 14.5 GB of memory with Q4_K_M quantization.
The recommended quantization for starcoder2 15b instruct v0.1 is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 6000 24GB, starcoder2 15b instruct v0.1 achieves approximately 50.7 tokens per second decode speed with a time-to-first-token of 3820ms using Q4_K_M quantization.
For coding workloads, starcoder2 15b instruct v0.1 on Quadro RTX 6000 24GB receives a C grade with 50.7 tok/s and 102K context.
On Quadro RTX 6000 24GB, starcoder2 15b instruct v0.1 can safely use up to 102K 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.
<iframe src="https://willitrunai.com/embed/hf-bartowski--starcoder2-15b-instruct-v0-1-gguf-on-quadro-rtx-6000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
8.4 GB |
| Medium |
| C47 |
Q4_K_M | 4 | 9.2 GB | Medium | C48 |
Q5_K_M | 5 | 10.8 GB | High | C49 |
Q6_K | 6 | 12.3 GB | High | C50 |
Q8_0Best for your GPU | 8 | 16.1 GB | Very High | C49 |
F16 | 16 | 30.7 GB | Maximum | F0 |