CodeLlama 13B Instruct needs ~26.1 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~59 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
58.5 tok/s
TTFT
3311 ms
Safe context
16K
Memory
26.1 GB / 48.0 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 | A | Runs well | 58.5 tok/s | 1806 ms | 16K |
| Coding | A | Runs well | 58.5 tok/s | 3311 ms | 16K |
| Agentic Coding | A | Runs well | 58.5 tok/s | 4816 ms | 16K |
| Reasoning | A | Runs well | 58.5 tok/s | 3913 ms | 16K |
| RAG | A | Runs well | 58.5 tok/s | 6020 ms | 16K |
How CodeLlama 13B Instruct (13B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.1 GB | Low | B67 |
Q3_K_S | 3 | 6.4 GB | Low | B67 |
NVFP4 | 4 |
Copy-paste commands to run CodeLlama 13B Instruct on your machine.
Run
lms load CodeLlama-13b-Instruct-hf && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 70.1 tok/s | ||
| 27B | S | 30.4 tok/s |
Yes, Quadro RTX 8000 48GB can run CodeLlama 13B Instruct with a A grade (Runs well). Expected decode speed: 58.5 tok/s.
CodeLlama 13B Instruct (13B parameters) requires approximately 26.1 GB of memory with Q4_K_M quantization.
The recommended quantization for CodeLlama 13B Instruct is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 8000 48GB, CodeLlama 13B Instruct achieves approximately 58.5 tokens per second decode speed with a time-to-first-token of 3311ms using Q4_K_M quantization.
For coding workloads, CodeLlama 13B Instruct on Quadro RTX 8000 48GB receives a A grade with 58.5 tok/s and 16K context.
On Quadro RTX 8000 48GB, CodeLlama 13B Instruct can safely use up to 16K tokens of context. The model's official context limit is 16K, 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/codellama-13b-instruct-on-quadro-rtx-8000-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
7.3 GB |
| Medium |
| B67 |
Q4_K_M | 4 | 7.9 GB | Medium | B67 |
Q5_K_M | 5 | 9.4 GB | High | B68 |
Q6_K | 6 | 10.7 GB | High | B68 |
Q8_0 | 8 | 13.9 GB | Very High | B69 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | A73 |
| 27B | S | 30.5 tok/s |
| 35B | S | 58.9 tok/s |
| 30B | S | 72.5 tok/s |