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 45 of the 125 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q4_K_M, at about 14 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 two of them run
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 |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q4_K_M | fits | 21.9 GB | 77k136k with q8 cache | 14tok/sest. | 192 tok/s | chat |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | fits | 21.3 GB | 86k150k with q8 cache | 15tok/sest. | 192 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | fits | 21.2 GB | 87k152k with q8 cache | 15tok/sest. | 192 tok/s | chat |
| Gemma 4 26B-A4B | UD-Q5_K_M | fits | 22.6 GB | 71k116k with q8 cache | 39tok/sest. | 1181 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | fits | 21.8 GB | 80k139k with q8 cache | 29tok/sest. | 572 tok/s | chat, coding, agents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.3 GB | 128k | 46tok/sest. | 883 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.6 GB | 256k | 22tok/sest. | 454 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.4 GB | 256k | 27tok/sest. | 556 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q4_K_M | fits | 22.3 GB | 70k128k with q8 cache | 14tok/sest. | 215 tok/s | chat |
| Ministral 3 14B Mistral AI | Q6_K | fits | 21.8 GB | 70k127k with q8 cache | 14tok/sest. | 266 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q6_K | fits | 22.8 GB | 40k | 14tok/sest. | 233 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.6 GB | 92k128k with q8 cache | 17tok/sest. | 367 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.6 GB | 40k | 17tok/sest. | 367 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | fits | 22.3 GB | 16k | 14tok/sest. | 234 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.7 GB | 256k | 47tok/sest. | 963 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.4 GB | 95k173k with q8 cache | 17tok/sest. | 363 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 20.2 GB | 80k128k with q8 cache | 16tok/sest. | 336 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 10.9 GB | 128k | 31tok/sest. | 728 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.9 GB | 125k | 44tok/sest. | 1554 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.6 GB | 118k128k with q8 cache | 21tok/sest. | 395 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 32k | 234tok/sest. | 3446 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.0 GB | 256k | 191tok/sest. | 3906 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.6 GB | 256k | 138tok/sest. | 2130 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 5.0 GB | 128k | 83tok/sest. | 1427 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.6 GB | 128k | 57tok/sest. | 804 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.6 GB | 458k767k with q8 cache | 57tok/sest. | 987 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.4 GB | 128k | 52tok/sest. | 1440 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.8 GB | 256k | 46tok/sest. | 963 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.9 GB | 128k | 45tok/sest. | 975 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.9 GB | 32k | 45tok/sest. | 917 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 19.2 GB | 128k | 37tok/sest. | 990 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 20.0 GB | 128k | 35tok/sest. | 990 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.8 GB | 128k | 35tok/sest. | 612 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 10.1 GB | 128k | 34tok/sest. | 632 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.4 GB | 170k256k with q8 cache | 29tok/sest. | 606 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.7 GB | 32k | 29tok/sest. | 326 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | fits | 20.8 GB | 88k128k with q8 cache | 28tok/sest. | 890 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.5 GB | 128k | 26tok/sest. | 462 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.3 GB | 128k | 25tok/sest. | 312 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.9 GB | 64k | 22tok/sest. | 312 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.4 GB | 105k128k with q8 cache | 18tok/sest. | 395 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.4 GB | 95k173k with q8 cache | 17tok/sest. | 363 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q5_K_M | fits | 21.1 GB | 128k | 15tok/sest. | 193 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | fits | 21.8 GB | 68k126k with q8 cache | 14tok/sest. | 212 tok/s | chat, coding |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q6_K | fits | 21.8 GB | 70k127k with q8 cache | 14tok/sest. | 266 tok/s | chat |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 42.1 GB | – | 11tok/sest. | 285 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 48.2 GB | – | 13tok/sest. | 623 tok/s | chat |
| Gemma 4 31B | Q4_K_M | offload | 24.3 GB | 45k89k with q8 cache | 10tok/sest. | 168 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.3 GB | – | 15tok/sest. | 286 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 23.0 GB | 56k87k with q8 cache | 56tok/sest. | 1147 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 23.3 GB | 44k70k with q8 cache | 52tok/sest. | 1138 tok/s | chat, coding, agents, long documents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 48.2 GB | – | 15tok/sest. | 710 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.8 GB | 51k93k with q8 cache | 9tok/sest. | 179 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.5 GB | 3k4k with q8 cache | 61tok/sest. | 1395 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 30.0 GB | – | 35tok/sest. | 786 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.8 GB | 44k79k with q8 cache | 16tok/sest. | 392 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.9 GB | 12k23k with q8 cache | 3tok/sest. | 75 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.8 GB | 51k93k with q8 cache | 9tok/sest. | 179 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 36.0 GB | 12k23k with q8 cache | 3tok/sest. | 93 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.8 GB | 51k93k with q8 cache | 9tok/sest. | 181 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.8 GB | 40k | 9tok/sest. | 181 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.8 GB | 40k | 9tok/sest. | 181 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.8 GB | 51k93k with q8 cache | 9tok/sest. | 179 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 24.9 GB | 33k59k with q8 cache | 9tok/sest. | 182 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 34.3 GB | 19k35k with q8 cache | 3tok/sest. | 112 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 97.0 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.5 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.5 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 87.1 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 53.0 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 62.2 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 55.2 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 61.1 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 61.1 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 161.3 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 93.2 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 72.2 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 225.3 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.6 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 389.3 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.9 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.8 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 753.3 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 81.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 132.2 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.7 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 93.2 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?
- Qwen 3.8 27B (Q4_K_M) fits fully in its memory at 64k context and generates at about 14 tok/s, an estimate from its memory bandwidth. 45 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.