Can the RTX 4070 run OTel-2.0-LLM-31B-IT-QLoRA?
No. OTel-2.0-LLM-31B-IT-QLoRA needs about 19.8 GB at Q4_K_M (weights plus 1.8 GB runtime overhead), and the RTX 4070 has 12 GB, so it won't fit without offloading layers to system RAM, which is far slower.
Every quantization
OTel-2.0-LLM-31B-IT-QLoRA (31.3B) on 12 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 18 GB | 19.8 GB | Too big | - |
| Q5_K_M | 22 GB | 23.8 GB | Too big | - |
| Q8_0 | 33 GB | 34.8 GB | Too big | - |
| FP16 | 63 GB | 64.8 GB | Too big | - |
Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 4070's 504 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.
What to do instead
Two ways forward
Cheapest cards that run it
- NVIDIA Tesla P40 - 24 GB, ~$159
- AMD Radeon RX 7900 XT - 20 GB, ~$699
- NVIDIA RTX 3090 - 24 GB, ~$750
- AMD Radeon RX 7900 XTX - 24 GB, ~$849
Models that fit the RTX 4070
- Qwen3 14B - 14B, 8 GB at Q4
- Ornith-1.5-9B - 9.7B, 6 GB at Q4
- Ornith-1.5-9B-OBLITERATED - 9.7B, 6 GB at Q4
- Qwen3.5 9B - 9.7B, 6 GB at Q4
Compare
Same model, other hardware - and other models on this card
OTel-2.0-LLM-31B-IT-QLoRA on other hardware
- RTX 5090~57 tok/s
- RTX 5090 D~57 tok/s
- RTX 6000D~50 tok/s
- RTX 4090~35 tok/s
- Radeon RX 7900 XTX~31 tok/s
- RTX 3090~30 tok/s
- MacBook Pro 16" M4 Max~17 tok/s
- Arc Pro B60~15 tok/s
Also runs on the RTX 4070
- Qwen3 14B~36 tok/s
- Ornith-1.5-9B~48 tok/s
- Ornith-1.5-9B-OBLITERATED~48 tok/s
- Qwen3.5 9B~48 tok/s
- Llama 3.1 8B~53 tok/s
- Qwen3.5 4B~96 tok/s
- Qwen3-4B-Instruct-2507~145 tok/s
- Phi-4 Mini~116 tok/s
Frequently asked
Quick answers
Can the NVIDIA RTX 4070 run OTel-2.0-LLM-31B-IT-QLoRA?
No. OTel-2.0-LLM-31B-IT-QLoRA needs about 19.8 GB at Q4_K_M (weights plus 1.8 GB runtime overhead), and the RTX 4070 has 12 GB, so it won't fit without offloading layers to system RAM, which is far slower.
How much VRAM does OTel-2.0-LLM-31B-IT-QLoRA need?
About 18 GB of weights at Q4_K_M, 33 GB at Q8_0 and 63 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is OTel-2.0-LLM-31B-IT-QLoRA on the RTX 4070?
It doesn't fit in the RTX 4070's memory, so speed depends on how many layers you offload to system RAM - typically single-digit tokens per second or lower.