NVIDIA GeForce RTX 4070
12 GB · 504.2 GB/s · 200 W
In short
The NVIDIA GeForce RTX 4070 has 12 GB of GDDR6X memory with 504.2 GB/s of bandwidth, which sets how fast it generates text. At 64k context it runs 21 of the 125 open models we track fully in memory; the most capable is Gemma 4 12B at Q5_K_M, at about 32 tok/s (estimated). We have no current price for the NVIDIA GeForce RTX 4070 in the UK.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the UK, cheapest first. Buy links may earn us a commission.
No retailer in this market lists it right now.
What it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Gemma 4 12B | Q5_K_M | fits | 10.2 GB | 118k190k with q8 cache | 32tok/sest. | 454 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q6_K | fits | 10.1 GB | 99k165k with q8 cache | 32tok/sest. | 556 tok/s | chat, coding, long documents |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.3 GB | 174k256k with q8 cache | 47tok/sest. | 963 tok/s | chat, coding, long documents |
| Gemma 4 E4B | Q8_0 | fits | 10.5 GB | 91k128k with q8 cache | 31tok/sest. | 728 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | UD-Q6_K | fits | 10.7 GB | 77k125k with q8 cache | 46tok/sest. | 1554 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.3 GB | 32k | 234tok/sest. | 3446 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.6 GB | 256k | 191tok/sest. | 3906 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.2 GB | 256k | 138tok/sest. | 2130 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 4.6 GB | 128k | 83tok/sest. | 1427 tok/s | chat, coding, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q5_K_M | fits | 11.3 GB | 70k106k with q8 cache | 62tok/sest. | 1440 tok/s | chat, coding, agents, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.2 GB | 128k | 57tok/sest. | 804 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.2 GB | 190k319k with q8 cache | 57tok/sest. | 987 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.4 GB | 171k256k with q8 cache | 46tok/sest. | 963 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.5 GB | 124k128k with q8 cache | 45tok/sest. | 975 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.5 GB | 32k | 45tok/sest. | 917 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q4_K_M | fits | 9.3 GB | 110k128k with q8 cache | 35tok/sest. | 312 tok/s | chat, coding |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.4 GB | 87k128k with q8 cache | 35tok/sest. | 612 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 9.7 GB | 84k128k with q8 cache | 34tok/sest. | 632 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q6_K | fits | 10.4 GB | 80k128k with q8 cache | 31tok/sest. | 462 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.0 GB | 67k122k with q8 cache | 29tok/sest. | 606 tok/s | chat, coding, agents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.3 GB | 32k | 29tok/sest. | 326 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 20.5 GB | – | 5tok/sest. | 138 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 20.9 GB | – | 4tok/sest. | 137 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 23.9 GB | – | 4tok/sest. | 117 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 22.6 GB | – | 17tok/sest. | 794 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 20.8 GB | – | 5tok/sest. | 137 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 17.9 GB | – | 16tok/sest. | 907 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.9 GB | – | 16tok/sest. | 789 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 21.4 GB | – | 8tok/sest. | 403 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 126 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.1 GB | – | 20tok/sest. | 969 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 13.4 GB | – | 27tok/sest. | 797 tok/s | chat, coding, agents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.6 GB | – | 19tok/sest. | 572 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.4 GB | – | 6tok/sest. | 275 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.5 GB | – | 2tok/sest. | 57 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 21.9 GB | – | 4tok/sest. | 150 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 126 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.6 GB | – | 2tok/sest. | 70 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 18.7 GB | 18k34k with q8 cache | 6tok/sest. | 199 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 19.5 GB | 14k26k with q8 cache | 5tok/sest. | 171 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 14.8 GB | 41k74k with q8 cache | 10tok/sest. | 313 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 14.8 GB | 40k | 10tok/sest. | 313 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | offload | 21.9 GB | 12k16k with q8 cache | 4tok/sest. | 163 tok/s | chat |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 14.4 GB | 42k76k with q8 cache | 10tok/sest. | 314 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q4_K_M | offload | 16.2 GB | 34k62k with q8 cache | 8tok/sest. | 272 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q4_K_M | offload | 13.7 GB | 46k84k with q8 cache | 12tok/sest. | 352 tok/s | chat, coding |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 12.8 GB | 24k40k with q8 cache | 30tok/sest. | 920 tok/s | chat, coding |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 14.0 GB | – | 23tok/sest. | 871 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 13.7 GB | 46k84k with q8 cache | 12tok/sest. | 352 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 14.4 GB | 42k76k with q8 cache | 10tok/sest. | 314 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 14.5 GB | – | 10tok/sest. | 268 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 20.4 GB | – | 9tok/sest. | 642 tok/s | chat |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 18.1 GB | – | 6tok/sest. | 148 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 18.7 GB | 18k34k with q8 cache | 6tok/sest. | 199 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 21.4 GB | 12k22k with q8 cache | 4tok/sest. | 150 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 127 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 127 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 127 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.4 GB | – | 3tok/sest. | 126 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 24.5 GB | – | 3tok/sest. | 127 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 33.9 GB | – | 2tok/sest. | 83 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 96.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.1 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 86.7 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 41.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.6 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 47.8 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 61.8 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 39.9 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 54.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.8 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.5 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 160.9 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 92.8 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 225.7 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 71.8 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 224.9 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 225.7 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 388.9 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.5 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.4 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 752.9 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 81.0 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.5 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 131.8 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.3 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 92.8 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 4070
- Memory
- 12 GB GDDR6X
- Memory bus
- 192-bit
- Memory bandwidth
- 504.2 GB/s
- FP16 compute
- 29.146 TFLOPS
- Software
- CUDA
- Board power
- 200 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 4070 have for AI models?
- The NVIDIA GeForce RTX 4070 has 12 GB of GDDR6X memory with 504.2 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 4070 can run locally?
- Gemma 4 12B (Q5_K_M) fits fully in its memory at 64k context and generates at about 32 tok/s, an estimate from its memory bandwidth. 21 of the 125 models we track fit at that context.
- Can the NVIDIA GeForce RTX 4070 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 97 GB at 64k context, more than the NVIDIA GeForce RTX 4070 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 4070 cost in the UK?
- We have no current price for the NVIDIA GeForce RTX 4070 in the UK.
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.