internlm JanusCoder 14B needs ~13.8 GB VRAM. NVIDIA A10 24GB has 24.0 GB. With Q4_K_M quantization, expect ~55 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
54.8 tok/s
TTFT
3533 ms
Safe context
116K
Memory
13.8 GB / 24.0 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 | 54.8 tok/s | 1927 ms | 116K |
| Coding | C | Runs well | 54.8 tok/s | 3533 ms | 116K |
| Agentic Coding | C | Runs well | 54.8 tok/s | 5139 ms | 116K |
| Reasoning | C | Runs well | 54.8 tok/s | 4175 ms | 116K |
| RAG | C | Runs well | 54.8 tok/s | 6423 ms | 116K |
How internlm JanusCoder 14B (14B params) fits at each quantization level on NVIDIA A10 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C45 |
Q3_K_S | 3 | 6.9 GB | Low | C46 |
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 A10 24GB can run internlm JanusCoder 14B with a C grade (Runs well). Expected decode speed: 54.8 tok/s.
internlm JanusCoder 14B (14B parameters) requires approximately 13.8 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 A10 24GB, internlm JanusCoder 14B achieves approximately 54.8 tokens per second decode speed with a time-to-first-token of 3533ms using Q4_K_M quantization.
For coding workloads, internlm JanusCoder 14B on NVIDIA A10 24GB receives a C grade with 54.8 tok/s and 116K context.
On NVIDIA A10 24GB, internlm JanusCoder 14B can safely use up to 116K 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-a10-24gb" 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 |
| C47 |
Q4_K_M | 4 | 8.5 GB | Medium | C47 |
Q5_K_M | 5 | 10.1 GB | High | C48 |
Q6_K | 6 | 11.5 GB | High | C49 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | C50 |
F16 | 16 | 28.7 GB | Maximum | F0 |