Compare · GPUs
RTX 5070 vs RTX 5070 Ti for local LLMs
It runs 21 of 39 models fully in memory, against 16 for the RTX 5070, thanks to 16 GB of VRAM versus 12 GB. It is also about 26% faster on the models both can run.
It runs 21 of 39 models fully in memory, against 16 for the RTX 5070, thanks to 16 GB of VRAM versus 12 GB. It is also about 26% faster on the models both can run.
Every model at 8K context with the best quantization that fits. Offload assumes 32 GB of system RAM. Green marks the better result. Rows where the two differ come first.
| Model | RTX 5070 | RTX 5070 Ti |
|---|---|---|
| Gemma 3 12B | Offload~9.1 tok/sQ4_K_M | Runs~58 tok/sQ6_K |
| Phi-4 14B | Offload~7.5 tok/sQ4_K_M | Runs~56 tok/sQ5_K_M |
| Qwen3 14B | Offload~7.5 tok/sQ4_K_M | Runs~55 tok/sQ5_K_M |
| DeepSeek-R1 Distill 14B | Offload~7.5 tok/sQ4_K_M | Runs~55 tok/sQ5_K_M |
| gpt-oss 20B | Offload~13 tok/sQ4_K_M | Runs~120 tok/sQ4_K_M |
| Qwen3 0.6B | Runs~690 tok/sQ8_0 | Runs~920 tok/sQ8_0 |
| Gemma 3 1B | Runs~410 tok/sQ8_0 | Runs~550 tok/sQ8_0 |
| Llama 3.2 1B | Runs~340 tok/sQ8_0 | Runs~460 tok/sQ8_0 |
| Llama 3.2 3B | Runs~130 tok/sQ8_0 | Runs~170 tok/sQ8_0 |
| Phi-4 Mini 3.8B | Runs~110 tok/sQ8_0 | Runs~140 tok/sQ8_0 |
| Qwen3 4B | Runs~100 tok/sQ8_0 | Runs~140 tok/sQ8_0 |
| Gemma 3 4B | Runs~96 tok/sQ8_0 | Runs~130 tok/sQ8_0 |
| Qwen3.5 4B | Runs~88 tok/sQ8_0 | Runs~120 tok/sQ8_0 |
| Mistral 7B v0.3 | Runs~57 tok/sQ8_0 | Runs~76 tok/sQ8_0 |
| Qwen2.5-Coder 7B | Runs~54 tok/sQ8_0 | Runs~72 tok/sQ8_0 |
| Llama 3.1 8B | Runs~52 tok/sQ8_0 | Runs~69 tok/sQ8_0 |
| DeepSeek-R1 Distill 8B | Runs~52 tok/sQ8_0 | Runs~69 tok/sQ8_0 |
| Qwen3 8B | Runs~50 tok/sQ8_0 | Runs~67 tok/sQ8_0 |
| Qwen3.5 9B | Runs~57 tok/sQ6_K | Runs~59 tok/sQ8_0 |
| Gemma 4 12B | Runs~62 tok/sQ4_K_M | Runs~59 tok/sQ6_K |
| Mistral Nemo 12B | Runs~61 tok/sQ4_K_M | Runs~58 tok/sQ6_K |
| Codestral 22B | Offload~4.2 tok/sQ4_K_M | Offload~6.2 tok/sQ4_K_M |
| Mistral Small 3 24B | Offload~3.8 tok/sQ4_K_M | Offload~5.5 tok/sQ4_K_M |
| Devstral Small 24B | Offload~3.8 tok/sQ4_K_M | Offload~5.6 tok/sQ4_K_M |
| Gemma 4 26B-A4B (MoE) | Offload~12 tok/sQ4_K_M | Offload~15 tok/sQ4_K_M |
| Gemma 3 27B | Offload~3.1 tok/sQ4_K_M | Offload~4.3 tok/sQ4_K_M |
| Qwen3.6 27B | Offload~3.2 tok/sQ4_K_M | Offload~4.6 tok/sQ4_K_M |
| Qwen3 30B-A3B (MoE) | Offload~13 tok/sQ4_K_M | Offload~16 tok/sQ4_K_M |
| Qwen3-Coder 30B-A3B | Offload~13 tok/sQ4_K_M | Offload~16 tok/sQ4_K_M |
| Gemma 4 31B | Offload~2.6 tok/sQ4_K_M | Offload~3.6 tok/sQ4_K_M |
| Qwen3 32B | Offload~2.5 tok/sQ4_K_M | Offload~3.5 tok/sQ4_K_M |
| DeepSeek-R1 Distill 32B | Offload~2.5 tok/sQ4_K_M | Offload~3.5 tok/sQ4_K_M |
| Qwen2.5-Coder 32B | Offload~2.5 tok/sQ4_K_M | Offload~3.5 tok/sQ4_K_M |
| Qwen3.6 35B-A3B (MoE) | Offload~14 tok/sQ4_K_M | Offload~16 tok/sQ4_K_M |
| Llama 3.3 70B | Won’t fit | Won’t fit |
| DeepSeek-R1 Distill 70B | Won’t fit | Won’t fit |
| Llama 4 Scout 109B-A17B | Won’t fit | Won’t fit |
| gpt-oss 120B | Won’t fit | Won’t fit |
| Qwen3 235B-A22B (MoE) | Won’t fit | Won’t fit |
Which should you buy?
The RTX 5070 Ti is the better card for local AI. It runs 21 of 39 models fully in memory, against 16 for the RTX 5070, thanks to 16 GB of VRAM versus 12 GB. It is also about 26% faster on the models both can run.
Only the RTX 5070 Ti fits Gemma 3 12B, Phi-4 14B, Qwen3 14B, DeepSeek-R1 Distill 14B and gpt-oss 20B fully in memory.
See every result on its own page: RTX 5070 and RTX 5070 Ti.
Questions
Is the RTX 5070 or the RTX 5070 Ti better for running LLMs?
The RTX 5070 Ti is the better card for local AI. It runs 21 of 39 models fully in memory, against 16 for the RTX 5070, thanks to 16 GB of VRAM versus 12 GB. It is also about 26% faster on the models both can run.
Which models can the RTX 5070 Ti run that the RTX 5070 can't?
At 8K context, only the RTX 5070 Ti holds Gemma 3 12B, Phi-4 14B, Qwen3 14B, DeepSeek-R1 Distill 14B and gpt-oss 20B fully in VRAM.
Does the RTX 5070 or RTX 5070 Ti need anything else to run local AI?
Only the software. Install Ollama or LM Studio, pick a model that fits in VRAM, and it runs on the GPU. 32 GB of system RAM helps when a model spills over, but that path is much slower.
More comparisons
Estimates from memory size and bandwidth at 8K context. Real speed varies with software, drivers and settings.