NVIDIA GeForce RTX 3090 vs NVIDIA GeForce RTX 5060 Ti 8GB
For running models locally, priced in the UK. At 8k context the first runs 61 models fully in memory, the second 26.
In short
The NVIDIA GeForce RTX 3090 has more memory for models: 24 GB against 8 GB. At 8k context the NVIDIA GeForce RTX 3090 runs 61 of the models we track fully in memory and the NVIDIA GeForce RTX 5060 Ti 8GB 26; only the NVIDIA GeForce RTX 3090 holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 3090 is about 2.1× as fast as the NVIDIA GeForce RTX 5060 Ti 8GB (estimated, median across models). In the UK the NVIDIA GeForce RTX 3090 costs £1,330 at Amazon and the NVIDIA GeForce RTX 5060 Ti 8GB £505 at eBay: the NVIDIA GeForce RTX 5060 Ti 8GB is £825 cheaper.
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | NVIDIA GeForce RTX 3090 | NVIDIA GeForce RTX 5060 Ti 8GB |
|---|---|---|
| GPU | GeForce RTX 3090 | GeForce RTX 5060 Ti 8GB |
| Memory | 24 GB GDDR6X | 8 GB GDDR7 |
| Memory bus | 384-bit | 128-bit |
| Memory bandwidth | 936 GB/s | 448 GB/s |
| FP16 compute | 71 TFLOPS | 23.704 TFLOPS |
| Software | CUDA | CUDA |
| Board power | 350 W | 180 W |
| PCIe generation | Gen 4 | Gen 5 |
| PCIe lanes | x16 | x8 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | NVIDIA GeForce RTX 3090 | NVIDIA GeForce RTX 5060 Ti 8GB |
|---|---|---|
| Qwen 3.8 27B | 26tok/sUD-Q6_K | offload |
| Qwen 3.6 27B | 25tok/sQ6_K | offload |
| Gemma 4 31B | 25tok/sQ5_K_M | offload |
| Qwen 3.6 35B-A3B | 167tok/sQ4_K_M | offload |
| Qwen 3.5 27B | 25tok/sQ6_K | offload |
| Gemma 4 26B-A4B | 88tok/sUD-Q6_K | offload |
| Qwen 3.5 35B-A3B | 168tok/sQ4_K_M | offload |
| GLM 4.7 Flash | 87tok/sQ5_K_M | offload |
| Devstral Small 2 24B | 28tok/sQ6_K | offload |
| Nemotron 3.5 Lightning 30B-A3B | 151tok/sMXFP4 | offload |
| gpt-oss 20B | 132tok/sMXFP4 | offload |
| Qwen3 Coder 30B-A3B | 118tok/sQ5_K_M | offload |
| Qwen3 32B | 27tok/sQ4_K_M | offload |
| Gemma 4 12B | 44tok/sQ8_0 | offload |
| Qwen 3.5 9B | 59tok/sQ8_0 | 40tok/sQ5_K_M |
| Mistral Small 3.2 24B | 28tok/sQ6_K | offload |
| DeepSeek R1 Distill Qwen 32B | 26tok/sQ4_K_M | offload |
| Gemma 3 27B | 25tok/sQ6_K | offload |
| Ministral 3 14B | 37tok/sQ8_0 | offload |
| Qwen3 14B | 34tok/sQ8_0 | offload |
| DeepSeek R1 0528 Qwen3 8B | 59tok/sQ8_0 | 39tok/sQ5_K_M |
| Qwen3 8B | 59tok/sQ8_0 | 39tok/sQ5_K_M |
| Phi-4 14B | 34tok/sQ8_0 | offload |
| Qwen 3.5 4B | 121tok/sQ8_0 | 58tok/sQ8_0 |
| Ministral 3 8B | 57tok/sQ8_0 | 44tok/sQ4_K_M |
| Granite 4.2 8B | 54tok/sQ8_0 | 40tok/sQ4_K_M |
| Gemma 4 E4B | 69tok/sQ8_0 | 48tok/sQ5_K_M |
| LFM2.5 8B-A1B | 237tok/sQ8_0 | 144tok/sUD-Q5_K_M |
| Llama 3.1 8B | 76tok/sQ6_K | 41tok/sQ5_K_M |
| Qwen2.5 0.5B | 919tok/sQ8_0 | 440tok/sQ8_0 |
| Qwen3.5 0.8B | 623tok/sQ8_0 | 298tok/sQ8_0 |
| Qwen3.5 2B | 373tok/sQ5_K_M | 179tok/sQ5_K_M |
| LFM3 1.7B | 297tok/sQ8_0 | 142tok/sQ8_0 |
| DeepSeek R1 Distill Qwen 1.5B | 273tok/sQ8_0 | 130tok/sQ8_0 |
| MiniCPM5 2B | 191tok/sQ8_0 | 92tok/sQ8_0 |
| LFM2.5 2.6B | 172tok/sQ8_0 | 82tok/sQ8_0 |
| LFM2.5 VL 3B | 172tok/sQ8_0 | 82tok/sQ8_0 |
| Spark X2.5 4B | 171tok/smlx-4bit | 82tok/smlx-4bit |
| LFM2.5 24B A2B | 143tok/sQ6_K | offload |
| granite vision 4.1 4b | 135tok/sQ8_0 | 65tok/sQ8_0 |
| Ministral 3 3B Instruct 2512 | 128tok/sQ8_0 | 61tok/sQ8_0 |
| granite 4.2 3b | 127tok/sQ8_0 | 61tok/sQ8_0 |
| Mellum2.1 12B A2.5B Thinking | 123tok/sQ8_0 | offload |
| FrogNano 4B 2609 | 118tok/sQ8_0 | 56tok/sQ8_0 |
| Kimi VL A3B Thinking 2506 | 104tok/sQ8_0 | offload |
| Kimi VL A3B | 99tok/smlx-8bit | offload |
| DeepSeek R1 Distill Qwen 7B | 68tok/sQ8_0 | 41tok/sQ6_K |
| GLM 4 9B 0414 | 68tok/smlx-5bit | offload |
| DeepSeek R1 Distill Llama 8B | 60tok/sQ8_0 | 41tok/sQ5_K_M |
| Ministral 3 8B Reasoning 2512 | 57tok/sQ8_0 | 44tok/sQ4_K_M |
| GLM 4.6V Flash | 56tok/sQ8_0 | 43tok/sQ4_K_M |
| GLM 4.1V 9B Thinking | 48tok/smlx-8bit | offload |
| Ministral 3 14B Reasoning 2512 | 37tok/sQ8_0 | offload |
| DeepSeek R1 Distill Qwen 14B | 34tok/sQ8_0 | offload |
| Devstral Small 2507 | 32tok/sQ5_K_M | offload |
| Magistral Small 2507 | 32tok/sQ5_K_M | offload |
| Magistral Small 2509 | 32tok/sQ5_K_M | offload |
| Magistral Small 2506 | 28tok/sQ6_K | offload |
| Qwen3.8 27B OBLITERATED | 27tok/smlx-4bit | offload |
| granite 4.2 30b | 25tok/sQ5_K_M | offload |
| Muse Glimmer 30B | 25tok/sQ6_K | 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 |
| Llama 3.3 70B | offload | won't run |
| DeepSeek R1 Distill Llama 70B | offload | won't run |
| 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 |
| DeepSeek R1 | won't run | won't run |
| DeepSeek R1 0528 | won't run | won't run |
| DeepSeek R1 Zero | won't run | won't run |
| DeepSeek V3 | 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 or the NVIDIA GeForce RTX 5060 Ti 8GB?
- Choose the NVIDIA GeForce RTX 3090 to run bigger models. Choose the NVIDIA GeForce RTX 3090 for speed. Choose the NVIDIA GeForce RTX 5060 Ti 8GB to spend less.
- Which can run bigger models, the NVIDIA GeForce RTX 3090 or the NVIDIA GeForce RTX 5060 Ti 8GB?
- At 8k context the NVIDIA GeForce RTX 3090 runs 61 of the models we track fully in memory and the NVIDIA GeForce RTX 5060 Ti 8GB 26; only the NVIDIA GeForce RTX 3090 holds Qwen 3.8 27B.
- Which is faster for local AI, the NVIDIA GeForce RTX 3090 or the NVIDIA GeForce RTX 5060 Ti 8GB?
- On the models both run fully in memory, the NVIDIA GeForce RTX 3090 is about 2.1× as fast as the NVIDIA GeForce RTX 5060 Ti 8GB (estimated, median across models).
- What is the price difference between the NVIDIA GeForce RTX 3090 and the NVIDIA GeForce RTX 5060 Ti 8GB?
- In the UK the NVIDIA GeForce RTX 3090 costs £1,330 at Amazon and the NVIDIA GeForce RTX 5060 Ti 8GB £505 at eBay: the NVIDIA GeForce RTX 5060 Ti 8GB is £825 cheaper.
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