internlm JanusCoder 14B needs ~15.4 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~153 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
153.0 tok/s
TTFT
1266 ms
Safe context
256K
Memory
15.4 GB / 40.0 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 | 153.0 tok/s | 690 ms | 256K |
| Coding | C | Runs well | 153.0 tok/s | 1266 ms | 256K |
| Agentic Coding | C | Runs well | 153.0 tok/s | 1841 ms | 256K |
| Reasoning | C | Runs well | 153.0 tok/s | 1496 ms | 256K |
| RAG | C | Runs well | 153.0 tok/s | 2301 ms | 256K |
How internlm JanusCoder 14B (14B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C42 |
Q3_K_S | 3 | 6.9 GB | Low | C43 |
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, NVIDIA A100 40GB can run internlm JanusCoder 14B with a C grade (Runs well). Expected decode speed: 153.0 tok/s.
internlm JanusCoder 14B (14B parameters) requires approximately 15.4 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 NVIDIA A100 40GB, internlm JanusCoder 14B achieves approximately 153.0 tokens per second decode speed with a time-to-first-token of 1266ms using Q4_K_M quantization.
For coding workloads, internlm JanusCoder 14B on NVIDIA A100 40GB receives a C grade with 153.0 tok/s and 256K context.
On NVIDIA A100 40GB, internlm JanusCoder 14B can safely use up to 256K 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-a100-40gb" 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 |
| C43 |
Q4_K_M | 4 | 8.5 GB | Medium | C43 |
Q5_K_M | 5 | 10.1 GB | High | C44 |
Q6_K | 6 | 11.5 GB | High | C44 |
Q8_0 | 8 | 15.0 GB | Very High | C45 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | C48 |