internlm2 limarp chat 20b needs ~23.7 GB VRAM. NVIDIA H100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~231 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
230.7 tok/s
TTFT
839 ms
Safe context
400K
Memory
23.7 GB / 80.0 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 | 230.7 tok/s | 458 ms | 400K |
| Coding | C | Runs well | 230.7 tok/s | 839 ms | 400K |
| Agentic Coding | C | Runs well | 230.7 tok/s | 1221 ms | 400K |
| Reasoning | C | Runs well | 230.7 tok/s | 992 ms | 400K |
| RAG | C | Runs well | 230.7 tok/s | 1526 ms | 400K |
How internlm2 limarp chat 20b (20B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 7.8 GB | Low | D40 |
Q3_K_S | 3 | 9.8 GB | Low | D40 |
NVFP4 | 4 |
Copy-paste commands to run internlm2 limarp chat 20b on your machine.
Run
lms load hf-intervitens-archive--internlm2-limarp-chat-20b-gguf && lms server startYes, NVIDIA H100 80GB can run internlm2 limarp chat 20b with a C grade (Runs well). Expected decode speed: 230.7 tok/s.
internlm2 limarp chat 20b (20B parameters) requires approximately 23.7 GB of memory with Q4_K_M quantization.
The recommended quantization for internlm2 limarp chat 20b is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA H100 80GB, internlm2 limarp chat 20b achieves approximately 230.7 tokens per second decode speed with a time-to-first-token of 839ms using Q4_K_M quantization.
For coding workloads, internlm2 limarp chat 20b on NVIDIA H100 80GB receives a C grade with 230.7 tok/s and 400K context.
On NVIDIA H100 80GB, internlm2 limarp chat 20b can safely use up to 400K 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-intervitens-archive--internlm2-limarp-chat-20b-gguf-on-h100-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| D40 |
Q4_K_M | 4 | 12.2 GB | Medium | C40 |
Q5_K_M | 5 | 14.4 GB | High | C40 |
Q6_K | 6 | 16.4 GB | High | C41 |
Q8_0 | 8 | 21.4 GB | Very High | C42 |
F16Best for your GPU | 16 | 41.0 GB | Maximum | C46 |