starcoder2 15b instruct v0.1 needs ~21.7 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~147 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
146.6 tok/s
TTFT
1321 ms
Safe context
692K
Memory
21.7 GB / 96.0 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 | 146.6 tok/s | 720 ms | 692K |
| Coding | C | Runs well | 146.6 tok/s | 1321 ms | 692K |
| Agentic Coding | C | Runs well | 146.6 tok/s | 1921 ms | 692K |
| Reasoning | C | Runs well | 146.6 tok/s | 1561 ms | 692K |
| RAG | C | Runs well | 146.6 tok/s | 2401 ms | 692K |
How starcoder2 15b instruct v0.1 (15B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | D39 |
Q3_K_S | 3 | 7.4 GB | Low | D39 |
NVFP4 | 4 | 8.4 GB | Medium | D39 |
Q4_K_M | 4 | 9.2 GB | Medium | D39 |
Q5_K_M | 5 | 10.8 GB | High | D39 |
Q6_K | 6 | 12.3 GB | High | D39 |
Q8_0 | 8 | 16.1 GB | Very High | D40 |
F16Best for your GPU | 16 | 30.7 GB | Maximum | C42 |
Copy-paste commands to run starcoder2 15b instruct v0.1 on your machine.
Run
lms load hf-lmstudio-community--starcoder2-15b-instruct-v0-1-gguf && lms server startYes, RTX PRO 6000 Blackwell Server Edition 96GB can run starcoder2 15b instruct v0.1 with a C grade (Runs well). Expected decode speed: 146.6 tok/s.
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 21.7 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 RTX PRO 6000 Blackwell Server Edition 96GB, starcoder2 15b instruct v0.1 achieves approximately 146.6 tokens per second decode speed with a time-to-first-token of 1321ms using Q4_K_M quantization.
For coding workloads, starcoder2 15b instruct v0.1 on RTX PRO 6000 Blackwell Server Edition 96GB receives a C grade with 146.6 tok/s and 692K context.
On RTX PRO 6000 Blackwell Server Edition 96GB, starcoder2 15b instruct v0.1 can safely use up to 692K 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-lmstudio-community--starcoder2-15b-instruct-v0-1-gguf-on-rtx-pro-6000-blackwell-server-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: