internlm JanusCoder 14B needs ~12.7 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~72 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
75.1 tok/s
TTFT
2578 ms
Safe context
48K
Memory
12.7 GB / 16.0 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 | B | Runs well | 75.1 tok/s | 1406 ms | 48K |
| Coding | B | Runs well | 71.5 tok/s | 2706 ms | 48K |
| Agentic Coding | C | Tight fit | 75.1 tok/s | 3749 ms | 48K |
| Reasoning | B | Runs well | 75.1 tok/s | 3046 ms | 48K |
| RAG | C | Tight fit | 75.1 tok/s | 4687 ms | 48K |
How internlm JanusCoder 14B (14B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C49 |
Q3_K_S | 3 | 6.9 GB | Low | C50 |
NVFP4 | 4 |
Copy-paste commands to run internlm JanusCoder 14B on your machine.
Run
lms load hf-bartowski--internlm-januscoder-14b-gguf && lms server startYes, RTX 4080 Super 16GB can run internlm JanusCoder 14B with a B grade (Runs well). Expected decode speed: 71.5 tok/s.
internlm JanusCoder 14B (14B parameters) requires approximately 12.7 GB of memory with Q4_K_M quantization.
The recommended quantization for internlm JanusCoder 14B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Super 16GB, internlm JanusCoder 14B achieves approximately 71.5 tokens per second decode speed with a time-to-first-token of 2706ms using Q4_K_M quantization.
For coding workloads, internlm JanusCoder 14B on RTX 4080 Super 16GB receives a B grade with 71.5 tok/s and 48K context.
On RTX 4080 Super 16GB, internlm JanusCoder 14B can safely use up to 48K 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-bartowski--internlm-januscoder-14b-gguf-on-rtx-4080-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
7.8 GB |
| Medium |
| C51 |
Q4_K_M | 4 | 8.5 GB | Medium | C51 |
Q5_K_M | 5 | 10.1 GB | High | C51 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | C50 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |