~$2,499 MSRP
internlm JanusCoder 14B needs ~14.3 GB VRAM. Radeon Pro W7800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~40 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
39.8 tok/s
TTFT
4865 ms
Safe context
189K
Memory
14.3 GB / 32.0 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 | 39.8 tok/s | 2654 ms | 189K |
| Coding | C | Runs well | 39.8 tok/s | 4865 ms | 189K |
| Agentic Coding | C | Runs well | 39.8 tok/s | 7076 ms | 189K |
| Reasoning | C | Runs well | 39.8 tok/s | 5750 ms | 189K |
| RAG | C | Runs well | 39.8 tok/s | 8846 ms | 189K |
How internlm JanusCoder 14B (14B params) fits at each quantization level on Radeon Pro W7800 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C43 |
Q3_K_S | 3 | 6.9 GB | Low | C44 |
NVFP4 | 4 |
Copy-paste commands to run internlm JanusCoder 14B on your machine.
Run
lms load hf-bartowski--internlm-januscoder-14b-gguf && lms server startUpgrade options
~$2,499 MSRP
Raises estimated decode speed by about 232%.
Adds memory headroom for longer context windows and future model growth.
~$4,999 MSRP
Yes, Radeon Pro W7800 32GB can run internlm JanusCoder 14B with a C grade (Runs well). Expected decode speed: 39.8 tok/s.
internlm JanusCoder 14B (14B parameters) requires approximately 14.3 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 Radeon Pro W7800 32GB, internlm JanusCoder 14B achieves approximately 39.8 tokens per second decode speed with a time-to-first-token of 4865ms using Q4_K_M quantization.
For coding workloads, internlm JanusCoder 14B on Radeon Pro W7800 32GB receives a C grade with 39.8 tok/s and 189K context.
On Radeon Pro W7800 32GB, internlm JanusCoder 14B can safely use up to 189K 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-radeon-pro-w7800-32gb" 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 |
| C44 |
Q4_K_M | 4 | 8.5 GB | Medium | C45 |
Q5_K_M | 5 | 10.1 GB | High | C45 |
Q6_K | 6 | 11.5 GB | High | C46 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | C48 |
F16 | 16 | 28.7 GB | Maximum | F0 |