starcoder2 15b instruct v0.1 needs ~24.6 GB VRAM. AMD Instinct MI300A 128GB has 128.0 GB. With Q4_K_M quantization, expect ~210 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
210.0 tok/s
TTFT
922 ms
Safe context
957K
Memory
24.6 GB / 128.0 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 | 210.0 tok/s | 503 ms | 957K |
| Coding | C | Runs well | 210.0 tok/s | 922 ms | 957K |
| Agentic Coding | C | Runs well | 210.0 tok/s | 1341 ms | 957K |
| Reasoning | C | Runs well | 210.0 tok/s | 1090 ms | 957K |
| RAG | C | Runs well | 210.0 tok/s | 1676 ms | 957K |
How starcoder2 15b instruct v0.1 (15B params) fits at each quantization level on AMD Instinct MI300A 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | D38 |
Q3_K_S | 3 | 7.4 GB | Low | D38 |
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, AMD Instinct MI300A 128GB can run starcoder2 15b instruct v0.1 with a C grade (Runs well). Expected decode speed: 210.0 tok/s.
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 24.6 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 AMD Instinct MI300A 128GB, starcoder2 15b instruct v0.1 achieves approximately 210.0 tokens per second decode speed with a time-to-first-token of 922ms using Q4_K_M quantization.
For coding workloads, starcoder2 15b instruct v0.1 on AMD Instinct MI300A 128GB receives a C grade with 210.0 tok/s and 957K context.
On AMD Instinct MI300A 128GB, starcoder2 15b instruct v0.1 can safely use up to 957K 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-instinct-mi300a-128gb" 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 |
| D38 |
Q4_K_M | 4 | 9.2 GB | Medium | D38 |
Q5_K_M | 5 | 10.8 GB | High | D38 |
Q6_K | 6 | 12.3 GB | High | D38 |
Q8_0 | 8 | 16.1 GB | Very High | D38 |
F16Best for your GPU | 16 | 30.7 GB | Maximum | C40 |