Can I Run InternLM 3 on NVIDIA GeForce RTX 5060 Ti 16GB?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Yes, but it's tight — InternLM 3 20B Instruct at Q4_K_M needs 14.5 GB at 8K context (12.1 GB weights + 2.4 GB KV cache/overhead), leaving ~1.5 GB of the NVIDIA GeForce RTX 5060 Ti 16GB's 16 GB, at ~28 tok/s (est.), with room for up to 8K context.
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NVIDIA GeForce RTX 5060 Ti 16GB Specs
| VRAM | 16 GB |
| Memory Bandwidth | 448 GB/s |
InternLM 3 20B Instruct on the NVIDIA GeForce RTX 5060 Ti 16GB: VRAM by quantization
| Quant | VRAM needed | Fits 16 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 42.4 GB | ✗ No | — | — |
| Q8_0 | 23.6 GB | ✗ No | — | Build for this |
| Q6_K | 18.8 GB | ✗ No | — | — |
| Q5_K_M | 16.6 GB | ✗ No | — | — |
| Q4_K_M | 14.5 GB | ✓ Yes | 8K | Build for this |
| Q3_K_M | 10.9 GB | ✓ Yes | 32K | — |
| Q2_K | 9 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 5060 Ti 16GB: 8K 14.5 GB · 32K 19.2 GB ✗. Past 32K it no longer fits 16 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? InternLM 3 20B Instruct on 24 GB of system RAM, CPU only: runs.
InternLM 3 Sizes That Fit the NVIDIA GeForce RTX 5060 Ti 16GB (at 8K context)
| InternLM 3 20B Instruct | Q4_K_M · 14.5 GB at 8K context · ~28 tok/s (est.) |
| InternLM 3 8B Instruct | Q4_K_M · 6.5 GB at 8K context · ~60 tok/s (est.) |
At 2 hrs/day, buying (~$429) beats renting at $0.34/hr after about 21 months.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Can I run InternLM 3 on the NVIDIA GeForce RTX 5060 Ti 16GB?
Yes, but it's tight — InternLM 3 20B Instruct at Q4_K_M needs 14.5 GB at 8K context (12.1 GB weights + 2.4 GB KV cache/overhead), leaving ~1.5 GB of the NVIDIA GeForce RTX 5060 Ti 16GB's 16 GB, at ~28 tok/s (est.), with room for up to 8K context.
What's the best InternLM 3 size for the NVIDIA GeForce RTX 5060 Ti 16GB?
InternLM 3 20B Instruct at Q4_K_M quantization needs 14.5 GB at 8K context (12.1 GB weights + 2.4 GB KV cache/overhead), estimated ~28 tokens/sec, up to 8K context.
Every InternLM 3 size on the NVIDIA GeForce RTX 5060 Ti 16GB
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| InternLM 3 20B Instruct | 14.5 GB | Runs | ~28 tok/s |
| InternLM 3 8B Instruct | 6.5 GB | Runs | ~60 tok/s |
InternLM 3 on Other GPUs
- InternLM 3 on NVIDIA GeForce RTX 5080
- InternLM 3 on NVIDIA GeForce RTX 5070 Ti
- InternLM 3 on NVIDIA GeForce RTX 4080 Super
- InternLM 3 on NVIDIA GeForce RTX 4080
- InternLM 3 on NVIDIA GeForce RTX 4070 Ti Super
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VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
← Can I Run It? | InternLM 3 Model Page | NVIDIA GeForce RTX 5060 Ti 16GB GPU Page | VRAM calculator | Check Your Hardware