starcoder2 15b instruct v0.1 needs ~14.1 GB VRAM. RTX A4500 20GB has 20.0 GB. With Q4_K_M quantization, expect ~55 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
54.6 tok/s
TTFT
3549 ms
Safe context
70K
Memory
14.1 GB / 20.0 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 | 54.6 tok/s | 1936 ms | 70K |
| Coding | C | Runs well | 54.6 tok/s | 3549 ms | 70K |
| Agentic Coding | C | Runs well | 54.6 tok/s | 5162 ms | 70K |
| Reasoning | C | Runs well | 54.6 tok/s | 4194 ms | 70K |
| RAG | C | Runs well | 54.6 tok/s | 6452 ms | 70K |
How starcoder2 15b instruct v0.1 (15B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C47 |
Q3_K_S | 3 | 7.4 GB | Low | C48 |
NVFP4 | 4 |
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 A4500 20GB can run starcoder2 15b instruct v0.1 with a C grade (Runs well). Expected decode speed: 54.6 tok/s.
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 14.1 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 A4500 20GB, starcoder2 15b instruct v0.1 achieves approximately 54.6 tokens per second decode speed with a time-to-first-token of 3549ms using Q4_K_M quantization.
For coding workloads, starcoder2 15b instruct v0.1 on RTX A4500 20GB receives a C grade with 54.6 tok/s and 70K context.
On RTX A4500 20GB, starcoder2 15b instruct v0.1 can safely use up to 70K 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-a4500-20gb" 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 |
| C49 |
Q4_K_M | 4 | 9.2 GB | Medium | C50 |
Q5_K_M | 5 | 10.8 GB | High | C50 |
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 |