CodeLlama 7B Instruct needs ~15.7 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~48 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
47.8 tok/s
TTFT
4050 ms
Safe context
16K
Memory
15.7 GB / 24.0 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 | 47.8 tok/s | 2209 ms | 16K |
| Coding | A | Runs well | 47.8 tok/s | 4050 ms | 16K |
| Agentic Coding | A | Runs with offload | 47.8 tok/s | 5890 ms | 16K |
| Reasoning | A | Runs well | 47.8 tok/s | 4786 ms | 16K |
| RAG | A | Runs with offload | 47.8 tok/s | 7363 ms | 16K |
How CodeLlama 7B Instruct (7B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B68 |
Q3_K_S | 3 | 3.4 GB | Low | B68 |
NVFP4 | 4 |
Copy-paste commands to run CodeLlama 7B Instruct on your machine.
Run
lms load CodeLlama-7b-Instruct-hf && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 30.9 tok/s | ||
| 27B | S | 13.4 tok/s |
Yes, Tesla P40 24GB can run CodeLlama 7B Instruct with a A grade (Runs well). Expected decode speed: 47.8 tok/s.
CodeLlama 7B Instruct (7B parameters) requires approximately 15.7 GB of memory with Q4_K_M quantization.
The recommended quantization for CodeLlama 7B Instruct is Q4_K_M, which balances quality and memory efficiency.
On Tesla P40 24GB, CodeLlama 7B Instruct achieves approximately 47.8 tokens per second decode speed with a time-to-first-token of 4050ms using Q4_K_M quantization.
For coding workloads, CodeLlama 7B Instruct on Tesla P40 24GB receives a A grade with 47.8 tok/s and 16K context.
On Tesla P40 24GB, CodeLlama 7B 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-7b-instruct-on-tesla-p40-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| B68 |
Q4_K_M | 4 | 4.3 GB | Medium | B68 |
Q5_K_M | 5 | 5.0 GB | High | B69 |
Q6_K | 6 | 5.7 GB | High | B69 |
Q8_0 | 8 | 7.5 GB | Very High | A70 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | A73 |
| 27B | S | 13.4 tok/s |
| 30B | S | 31.9 tok/s |
| 9B | S | 40 tok/s |