InternLM 20B needs ~38.4 GB VRAM. RTX 6000 Ada 48GB has 48.0 GB. With Q5_K_M quantization, expect ~56 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
55.8 tok/s
TTFT
3472 ms
Safe context
8K
Memory
38.4 GB / 48.0 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 | B | Runs well | 55.8 tok/s | 1894 ms | 8K |
| Coding | B | Runs well | 55.8 tok/s | 3472 ms | 8K |
| Agentic Coding | C | Very compromised (needs ~2.2 GB host RAM) | 29.4 tok/s | 9569 ms | 8K |
| Reasoning | B | Runs well | 55.8 tok/s | 4103 ms | 8K |
| RAG | C | Very compromised (needs ~2.2 GB host RAM) | 29.4 tok/s | 11961 ms | 8K |
How InternLM 20B (20B params) fits at each quantization level on RTX 6000 Ada 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 7.8 GB | Low | C50 |
Q3_K_S | 3 | 9.8 GB | Low | C51 |
NVFP4 | 4 |
Copy-paste commands to run InternLM 20B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "internlm/internlm2_5-20b-chat" \
--hf-file "internlm2_5-20b-chat-Q5_K_M.gguf" \
-c 4096 -ngl 99Yes, RTX 6000 Ada 48GB can run InternLM 20B with a B grade (Runs well). Expected decode speed: 55.8 tok/s.
InternLM 20B (20B parameters) requires approximately 38.4 GB of memory with Q5_K_M quantization.
The recommended quantization for InternLM 20B is Q5_K_M, which balances quality and memory efficiency.
On RTX 6000 Ada 48GB, InternLM 20B achieves approximately 55.8 tokens per second decode speed with a time-to-first-token of 3472ms using Q5_K_M quantization.
For coding workloads, InternLM 20B on RTX 6000 Ada 48GB receives a B grade with 55.8 tok/s and 8K context.
On RTX 6000 Ada 48GB, InternLM 20B can safely use up to 8K tokens of context. The model's official context limit is 8K, 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/internlm-20b-on-rtx-6000-ada-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
11.2 GB |
| Medium |
| C51 |
Q4_K_M | 4 | 12.2 GB | Medium | C51 |
Q5_K_M | 5 | 14.4 GB | High | C52 |
Q6_K | 6 | 16.4 GB | High | C53 |
Q8_0 | 8 | 21.4 GB | Very High | C54 |
F16Best for your GPU | 16 | 41.0 GB | Maximum | B56 |