RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pick1792 GB/s (+992)
C
Raises estimated decode speed by about 242%.155.2 tok/s decode
Raises estimated decode speed by about 242%.
~$9,999 MSRP
StarCoder2 15B needs ~26.7 GB VRAM. Mac Studio M1 Ultra 128GB has 92.2 GB. With Q5_K_M quantization, expect ~45 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
45.4 tok/s
TTFT
4268 ms
Safe context
16K
Memory
26.7 GB / 92.2 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 45.4 tok/s | 2328 ms | 16K |
| Coding | C | Runs well | 45.4 tok/s | 4268 ms | 16K |
| Agentic Coding | C | Runs well | 45.4 tok/s | 6207 ms | 16K |
| Reasoning | C | Runs well | 45.4 tok/s | 5044 ms | 16K |
| RAG | C | Runs well | 45.4 tok/s | 7759 ms | 16K |
How StarCoder2 15B (15B params) fits at each quantization level on Mac Studio M1 Ultra 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C41 |
Q3_K_S | 3 | 7.4 GB | Low | C41 |
NVFP4 | 4 | 8.4 GB | Medium | C41 |
Q4_K_M | 4 | 9.2 GB | Medium | C41 |
Q5_K_M | 5 | 10.8 GB | High | C41 |
Q6_K | 6 | 12.3 GB | High | C41 |
Q8_0 | 8 | 16.1 GB | Very High | C42 |
F16Best for your GPU | 16 | 30.7 GB | Maximum | C44 |
Copy-paste commands to run StarCoder2 15B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "bigcode/starcoder2-15b" \
--hf-file "starcoder2-15b-Q5_K_M.gguf" \
-c 4096 -ngl 99Upgrade options
RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pickRaises estimated decode speed by about 242%.
~$9,999 MSRP
RTX PRO 6000 Blackwell Server Edition 96GBBest valueRaises estimated decode speed by about 205%.
~$9,999 MSRP
Yes, Mac Studio M1 Ultra 128GB can run StarCoder2 15B with a C grade (Runs well). Expected decode speed: 45.4 tok/s.
StarCoder2 15B (15B parameters) requires approximately 26.7 GB of memory with Q5_K_M quantization.
The recommended quantization for StarCoder2 15B is Q5_K_M, which balances quality and memory efficiency.
On Mac Studio M1 Ultra 128GB, StarCoder2 15B achieves approximately 45.4 tokens per second decode speed with a time-to-first-token of 4268ms using Q5_K_M quantization.
For coding workloads, StarCoder2 15B on Mac Studio M1 Ultra 128GB receives a C grade with 45.4 tok/s and 16K context.
On Mac Studio M1 Ultra 128GB, StarCoder2 15B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.
Not always. Mac Studio M1 Ultra 128GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/starcoder2-15b-on-m1-ultra-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: