NVIDIA GeForce RTX 3090 Ti vs NVIDIA GeForce RTX 4070 Super
For running models locally, priced in Germany. At 32k context the first runs 54 models fully in memory, the second 27.
In short
The NVIDIA GeForce RTX 3090 Ti has more memory for models: 24 GB against 12 GB. At 32k context the NVIDIA GeForce RTX 3090 Ti runs 54 of the models we track fully in memory and the NVIDIA GeForce RTX 4070 Super 27; only the NVIDIA GeForce RTX 3090 Ti holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 3090 Ti is about 2.0× as fast as the NVIDIA GeForce RTX 4070 Super (estimated, median across models). In Germany the NVIDIA GeForce RTX 3090 Ti costs 1.799 € at eBay (used) and the NVIDIA GeForce RTX 4070 Super 1.800 € at eBay: the NVIDIA GeForce RTX 3090 Ti is 1 € cheaper.
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | NVIDIA GeForce RTX 3090 Ti | NVIDIA GeForce RTX 4070 Super |
|---|---|---|
| GPU | GeForce RTX 3090 Ti | GeForce RTX 4070 Super |
| Memory | 24 GB GDDR6X | 12 GB GDDR6X |
| Memory bus | 384-bit | 192-bit |
| Memory bandwidth | 1,008 GB/s | 504 GB/s |
| FP16 compute | 80 TFLOPS | 71 TFLOPS |
| Software | CUDA | CUDA |
| Board power | 450 W | 220 W |
| PCIe generation | Gen 4 | Gen 4 |
| PCIe lanes | x16 | x16 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | NVIDIA GeForce RTX 3090 Ti | NVIDIA GeForce RTX 4070 Super |
|---|---|---|
| Qwen 3.8 27B | 27tok/sQ5_K_M | offload |
| Qwen 3.6 27B | 29tok/sQ5_K_M | offload |
| Gemma 4 31B | 29tok/sQ4_K_M | offload |
| Qwen 3.6 35B-A3B | 145tok/sQ4_K_M | offload |
| Qwen 3.5 27B | 29tok/sQ5_K_M | offload |
| Gemma 4 26B-A4B | 84tok/sUD-Q6_K | offload |
| Qwen 3.5 35B-A3B | 146tok/sQ4_K_M | offload |
| GLM 4.7 Flash | 70tok/sQ5_K_M | offload |
| Devstral Small 2 24B | 28tok/sQ5_K_M | offload |
| Nemotron 3.5 Lightning 30B-A3B | 153tok/sMXFP4 | offload |
| gpt-oss 20B | 116tok/sMXFP4 | offload |
| Qwen3 Coder 30B-A3B | 74tok/sQ4_K_M | offload |
| Gemma 4 12B | 46tok/sQ8_0 | 29tok/sQ6_K |
| Qwen 3.5 9B | 59tok/sQ8_0 | 29tok/sQ8_0 |
| Mistral Small 3.2 24B | 28tok/sQ5_K_M | offload |
| Gemma 3 27B | 28tok/sQ5_K_M | offload |
| Ministral 3 14B | 32tok/sQ8_0 | offload |
| Qwen3 14B | 30tok/sQ8_0 | offload |
| DeepSeek R1 0528 Qwen3 8B | 46tok/sQ8_0 | 29tok/sQ5_K_M |
| Qwen3 8B | 46tok/sQ8_0 | 29tok/sQ5_K_M |
| Phi-4 14B | 28tok/sQ8_0 | offload |
| Qwen 3.5 4B | 112tok/sQ8_0 | 56tok/sQ8_0 |
| Ministral 3 8B | 46tok/sQ8_0 | 29tok/sQ5_K_M |
| Granite 4.2 8B | 43tok/sQ8_0 | 29tok/sQ4_K_M |
| Gemma 4 E4B | 68tok/sQ8_0 | 34tok/sQ8_0 |
| LFM2.5 8B-A1B | 140tok/sQ8_0 | 70tok/sQ8_0 |
| Llama 3.1 8B | 57tok/sQ6_K | 29tok/sQ6_K |
| Qwen2.5 0.5B | 669tok/sQ8_0 | 335tok/sQ8_0 |
| Qwen3.5 0.8B | 507tok/sQ8_0 | 253tok/sQ8_0 |
| Qwen3.5 2B | 337tok/sQ5_K_M | 168tok/sQ5_K_M |
| DeepSeek R1 Distill Qwen 1.5B | 221tok/sQ8_0 | 110tok/sQ8_0 |
| MiniCPM5 2B | 153tok/sQ8_0 | 76tok/sQ8_0 |
| Spark X2.5 4B | 145tok/smlx-4bit | 73tok/smlx-4bit |
| LFM2.5 2.6B | 128tok/sQ8_0 | 64tok/sQ8_0 |
| LFM2.5 VL 3B | 128tok/sQ8_0 | 64tok/sQ8_0 |
| Mellum2.1 12B A2.5B Thinking | 118tok/sQ8_0 | 73tok/sQ5_K_M |
| FrogNano 4B 2609 | 109tok/sQ8_0 | 54tok/sQ8_0 |
| granite vision 4.1 4b | 99tok/sQ8_0 | 50tok/sQ8_0 |
| granite 4.2 3b | 95tok/sQ8_0 | 48tok/sQ8_0 |
| Kimi VL A3B Thinking 2506 | 91tok/sQ8_0 | offload |
| Kimi VL A3B | 88tok/smlx-8bit | offload |
| LFM2.5 24B A2B | 84tok/sQ6_K | offload |
| GLM 4 9B 0414 | 65tok/smlx-5bit | 33tok/smlx-5bit |
| DeepSeek R1 Distill Qwen 7B | 63tok/sQ8_0 | 31tok/sQ8_0 |
| GLM 4.6V Flash | 55tok/sQ8_0 | 42tok/sQ4_K_M |
| DeepSeek R1 Distill Llama 8B | 49tok/sQ8_0 | 29tok/sQ6_K |
| GLM 4.1V 9B Thinking | 48tok/smlx-8bit | offload |
| Ministral 3 8B Reasoning 2512 | 46tok/sQ8_0 | 29tok/sQ5_K_M |
| DeepSeek R1 Distill Qwen 14B | 28tok/sQ8_0 | offload |
| Devstral Small 2507 | 28tok/sQ5_K_M | offload |
| Magistral Small 2506 | 28tok/sQ5_K_M | offload |
| Magistral Small 2507 | 28tok/sQ5_K_M | offload |
| Magistral Small 2509 | 28tok/sQ5_K_M | offload |
| Qwen3.8 27B OBLITERATED | 27tok/smlx-4bit | offload |
| Qwen 3.5 122B-A10B | offload | won't run |
| Qwen3 Coder Next | offload | won't run |
| Mistral Small 4 119B | offload | won't run |
| GLM 4.5 Air | offload | won't run |
| Qwen3 Next 80B-A3B | offload | won't run |
| Kimi Linear 48B-A3B | offload | offload |
| Qwen3 32B | offload | offload |
| DeepSeek R1 Distill Qwen 32B | offload | offload |
| granite 4.2 30b | offload | offload |
| DeepSeek V4 Flash | won't run | won't run |
| GLM 5.3 Flash | won't run | won't run |
| Qwen 3.8 Flash Next | won't run | won't run |
| MiniMax M2.7 | won't run | won't run |
| Nemotron 3 Super 120B-A12B | won't run | won't run |
| gpt-oss 120B | won't run | won't run |
| Llama 3.3 70B | won't run | won't run |
| DeepSeek R1 | won't run | won't run |
| DeepSeek R1 0528 | won't run | won't run |
| DeepSeek R1 Distill Llama 70B | won't run | won't run |
| DeepSeek R1 Zero | won't run | won't run |
| DeepSeek V3 0324 | won't run | won't run |
| DeepSeek V3.1 | won't run | won't run |
| DeepSeek V3.1 Terminus | won't run | won't run |
| DeepSeek V3.2 | won't run | won't run |
| DeepSeek V4 Flash 0731 | won't run | won't run |
| DeepSeek V4 Flash Vision Exp | won't run | won't run |
| Devstral 2 123B Instruct 2512 | won't run | won't run |
| GLM 4.5 | won't run | won't run |
| GLM 4.5V | won't run | won't run |
| GLM 4.6 | won't run | won't run |
| GLM 4.6V | won't run | won't run |
| GLM 4.7 | won't run | won't run |
| GLM 5 | won't run | won't run |
| GLM 5.1 | won't run | won't run |
| GLM 5.2 | won't run | won't run |
| GLM 5.3 | won't run | won't run |
| Kimi Dev 72B | won't run | won't run |
| Kimi K2 | won't run | won't run |
| Kimi K2 Instruct 0905 | won't run | won't run |
| Kimi K2 Thinking | won't run | won't run |
| Kimi K2.5 | won't run | won't run |
| MiniMax M2 | won't run | won't run |
| MiniMax M2.1 | won't run | won't run |
| MiniMax M2.5 | won't run | won't run |
| MiniMax M3 | won't run | won't run |
| Mistral Medium 3.5 128B | won't run | won't run |
Questions
- Which is better for local AI, the NVIDIA GeForce RTX 3090 Ti or the NVIDIA GeForce RTX 4070 Super?
- Choose the NVIDIA GeForce RTX 3090 Ti to run bigger models. Choose the NVIDIA GeForce RTX 3090 Ti for speed. Choose the NVIDIA GeForce RTX 3090 Ti to spend less.
- Which can run bigger models, the NVIDIA GeForce RTX 3090 Ti or the NVIDIA GeForce RTX 4070 Super?
- At 32k context the NVIDIA GeForce RTX 3090 Ti runs 54 of the models we track fully in memory and the NVIDIA GeForce RTX 4070 Super 27; only the NVIDIA GeForce RTX 3090 Ti holds Qwen 3.8 27B.
- Which is faster for local AI, the NVIDIA GeForce RTX 3090 Ti or the NVIDIA GeForce RTX 4070 Super?
- On the models both run fully in memory, the NVIDIA GeForce RTX 3090 Ti is about 2.0× as fast as the NVIDIA GeForce RTX 4070 Super (estimated, median across models).
- What is the price difference between the NVIDIA GeForce RTX 3090 Ti and the NVIDIA GeForce RTX 4070 Super?
- In Germany the NVIDIA GeForce RTX 3090 Ti costs 1.799 € at eBay (used) and the NVIDIA GeForce RTX 4070 Super 1.800 € at eBay: the NVIDIA GeForce RTX 3090 Ti is 1 € cheaper.
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