Compatibility Check
Can I Run InternLM 2.5 20B on NVIDIA GeForce RTX 2080 Ti?
Sort of — NVIDIA GeForce RTX 2080 Ti can run InternLM 2.5 20B (Q4_K_M) only by spilling layers to RAM. Generation will be slow.
Estimated ~13 tokens/sec on the Q4_K_M quantization.
Hybrid CPU+GPU
Best variant: Q4_K_M
CPU + GPU hybrid — not enough VRAM (11 GB < 14 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.
- GPU VRAM
- 11 GB
- Min VRAM (best fit)
- 14 GB
- Recommended VRAM
- 16 GB
- Estimated tok/s
- ~13
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Every InternLM 2.5 20B quantization on NVIDIA GeForce RTX 2080 Ti
Each row runs the compatibility engine against your VRAM, RAM, and the model's requirements.
| Quantization | File Size | Min VRAM | Rec VRAM | Context | Verdict | Estimated tok/s |
|---|---|---|---|---|---|---|
| Q4_K_MBest fit | 12 GB | 14 GB | 16 GB | 8K / 32K | Hybrid CPU+GPU | ~13 |
Upgrade options that fit InternLM 2.5 20B better
Rent GPU instead of buying one
If local fit is weak, cloud GPU gets you running today without hardware upgrade.