internlm2 limarp chat 20b needs ~25.3 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~110 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
110.0 tok/s
TTFT
1761 ms
Safe context
498K
Memory
25.3 GB / 96.0 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 | 110.0 tok/s | 960 ms | 498K |
| Coding | C | Runs well | 110.0 tok/s | 1761 ms | 498K |
| Agentic Coding | C | Runs well | 110.0 tok/s | 2561 ms | 498K |
| Reasoning | C | Runs well | 110.0 tok/s | 2081 ms | 498K |
| RAG | C | Runs well | 110.0 tok/s | 3201 ms | 498K |
How internlm2 limarp chat 20b (20B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 7.8 GB | Low | D39 |
Q3_K_S | 3 | 9.8 GB | Low | D39 |
NVFP4 | 4 | 11.2 GB | Medium | D39 |
Q4_K_M | 4 | 12.2 GB | Medium | D39 |
Q5_K_M | 5 | 14.4 GB | High | D39 |
Q6_K | 6 | 16.4 GB | High | D40 |
Q8_0 | 8 | 21.4 GB | Very High | C40 |
F16Best for your GPU | 16 | 41.0 GB | Maximum | C44 |
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, RTX PRO 6000 Blackwell Server Edition 96GB can run internlm2 limarp chat 20b with a C grade (Runs well). Expected decode speed: 110.0 tok/s.
internlm2 limarp chat 20b (20B parameters) requires approximately 25.3 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 RTX PRO 6000 Blackwell Server Edition 96GB, internlm2 limarp chat 20b achieves approximately 110.0 tokens per second decode speed with a time-to-first-token of 1761ms using Q4_K_M quantization.
For coding workloads, internlm2 limarp chat 20b on RTX PRO 6000 Blackwell Server Edition 96GB receives a C grade with 110.0 tok/s and 498K context.
On RTX PRO 6000 Blackwell Server Edition 96GB, internlm2 limarp chat 20b can safely use up to 498K 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-rtx-pro-6000-blackwell-server-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: