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 8k context it runs 34 of the 125 open models we track fully in memory; the most capable is Gemma 4 12B at Q6_K, at about 31 tok/s (estimated). We have no current price for the NVIDIA GeForce RTX 4070 in Germany.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Germany, 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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Gemma 4 12B | Q6_K | fits | 10.3 GB | 59k100k with q8 cache | 31tok/sest. | 522 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 9.9 GB | 47k79k with q8 cache | 32tok/sest. | 661 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q4_K_M | fits | 10.4 GB | 14k26k with q8 cache | 30tok/sest. | 399 tok/s | chat |
| Ministral 3 14B Mistral AI | Q5_K_M | fits | 11.0 GB | 10k19k with q8 cache | 29tok/sest. | 429 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.0 GB | 17k32k with q8 cache | 32tok/sest. | 698 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.0 GB | 17k32k with q8 cache | 32tok/sest. | 698 tok/s | chat |
| Phi-4 14B Microsoft | Q4_K_M | fits | 10.6 GB | 12k16k with q8 cache | 30tok/sest. | 401 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.2 GB | 174k256k with q8 cache | 65tok/sest. | 1331 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.2 GB | 16k29k with q8 cache | 31tok/sest. | 652 tok/s | chat |
| Granite 4.2 8B IBM | Q8_0 | fits | 10.7 GB | 12k22k with q8 cache | 29tok/sest. | 647 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 8.6 GB | 91k128k with q8 cache | 37tok/sest. | 801 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.5 GB | 43k75k with q8 cache | 128tok/sest. | 4675 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q6_K | fits | 7.9 GB | 34k63k with q8 cache | 41tok/sest. | 720 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.3 GB | 32k | 495tok/sest. | 9785 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 1.6 GB | 256k | 336tok/sest. | 6732 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.2 GB | 256k | 201tok/sest. | 2762 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 2.7 GB | 128k | 147tok/sest. | 3080 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 3.6 GB | 128k | 103tok/sest. | 2036 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 3.9 GB | 124k128k with q8 cache | 93tok/sest. | 2049 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 3.9 GB | 32k | 93tok/sest. | 1808 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 3.9 GB | 190k319k with q8 cache | 92tok/sest. | 1449 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 10.8 GB | 24k40k with q8 cache | 86tok/sest. | 1899 tok/s | chat, coding |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q5_K_M | fits | 10.2 GB | 70k106k with q8 cache | 85tok/sest. | 2253 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 4.7 GB | 87k128k with q8 cache | 73tok/sest. | 1356 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.0 GB | 67k122k with q8 cache | 69tok/sest. | 1389 tok/s | chat, coding, agents |
| granite 4.2 3b IBM | Q8_0 | fits | 5.0 GB | 84k128k with q8 cache | 69tok/sest. | 1458 tok/s | chat, coding, agents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.3 GB | 171k256k with q8 cache | 63tok/sest. | 1331 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 8.7 GB | 52k90k with q8 cache | 37tok/sest. | 777 tok/s | chat, coding |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 8.7 GB | 32k | 36tok/sest. | 611 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 9.7 GB | 20k37k with q8 cache | 33tok/sest. | 720 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.2 GB | 16k29k with q8 cache | 31tok/sest. | 652 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 10.4 GB | 30k52k with q8 cache | 30tok/sest. | 564 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | fits | 10.6 GB | 12k22k with q8 cache | 30tok/sest. | 391 tok/s | chat |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q5_K_M | fits | 11.0 GB | 10k19k with q8 cache | 29tok/sest. | 429 tok/s | chat |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 16.7 GB | – | 7tok/sest. | 184 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 17.0 GB | – | 7tok/sest. | 182 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 19.2 GB | – | 5tok/sest. | 149 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.2 GB | – | 28tok/sest. | 1402 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 17.0 GB | – | 7tok/sest. | 182 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 16.5 GB | – | 25tok/sest. | 1207 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 21.5 GB | – | 27tok/sest. | 1393 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 18.2 GB | – | 19tok/sest. | 843 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 217 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 22.5 GB | – | 24tok/sest. | 1423 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 11.8 GB | – | 64tok/sest. | 1395 tok/s | chat, coding, agents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 28.8 GB | – | 24tok/sest. | 1173 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 18.8 GB | – | 24tok/sest. | 1073 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 21.2 GB | – | 4tok/sest. | 126 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 217 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 17.2 GB | – | 7tok/sest. | 183 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 21.2 GB | – | 4tok/sest. | 132 tok/s | – |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 12.0 GB | – | 62tok/sest. | 1838 tok/s | chat, coding, agents |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 15.7 GB | – | 40tok/sest. | 2034 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 12.0 GB | – | 20tok/sest. | 545 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 221 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 221 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 221 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 217 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.0 GB | – | 7tok/sest. | 168 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 19.5 GB | – | 5tok/sest. | 155 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 20.6 GB | – | 5tok/sest. | 166 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 91.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 74.5 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 72.8 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 40.0 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 51.9 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 46.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 59.5 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 38.4 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 44.4 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 46.2 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 42.8 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.4 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 42.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 155.8 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 73.3 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 61.4 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.4 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 67.8 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 383.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 747.8 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 63.2 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.4 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.0 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.4 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 73.3 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 (Q6_K) fits fully in its memory at 8k context and generates at about 31 tok/s, an estimate from its memory bandwidth. 34 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 92 GB at 8k context, more than the NVIDIA GeForce RTX 4070 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 4070 cost in Germany?
- We have no current price for the NVIDIA GeForce RTX 4070 in Germany.
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.