NVIDIA GeForce RTX 5070 Ti
16 GB · 896 GB/s · 300 W
Prices
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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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 28.8 GB | 36k64k with q8 cache | 19tok/sest. | 693 tok/s | chat |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 42k74k with q8 cache | 19tok/sest. | 693 tok/s | chat |
| Gemma 4 31B | Q6_K | fits | 26.0 GB | 64k122k with q8 cache | 21tok/sest. | 604 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 28.7 GB | 92k144k with q8 cache | 125tok/sest. | 5936 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 42k74k with q8 cache | 19tok/sest. | 693 tok/s | chat |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.5 GB | 176k256k with q8 cache | 73tok/sest. | 4523 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 28.2 GB | 109k170k with q8 cache | 126tok/sest. | 5936 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 24.6 GB | 116k198k with q8 cache | 74tok/sest. | 3322 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 39k71k with q8 cache | 21tok/sest. | 781 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.2 GB | 122k167k with q8 cache | 172tok/sest. | 5642 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.6 GB | 128k | 127tok/sest. | 4296 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 25.3 GB | 63k113k with q8 cache | 102tok/sest. | 4294 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q6_K | fits | 28.2 GB | 18k33k with q8 cache | 19tok/sest. | 534 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 13.4 GB | 256k | 42tok/sest. | 1576 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.3 GB | 256k | 56tok/sest. | 1996 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 39k71k with q8 cache | 21tok/sest. | 781 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q6_K | fits | 28.2 GB | 18k33k with q8 cache | 19tok/sest. | 559 tok/s | chat |
| Gemma 3 27B | Q8_0 | fits | 28.9 GB | 30k58k with q8 cache | 19tok/sest. | 702 tok/s | chat |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 15.8 GB | 100k183k with q8 cache | 35tok/sest. | 1295 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 17.0 GB | 40k | 33tok/sest. | 1204 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.4 GB | 128k | 56tok/sest. | 2107 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.4 GB | 40k | 56tok/sest. | 2107 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 17.2 GB | 16k | 32tok/sest. | 1212 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.6 GB | 256k | 116tok/sest. | 4018 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.6 GB | 153k256k with q8 cache | 55tok/sest. | 1968 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.1 GB | 128k | 52tok/sest. | 1954 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 9.0 GB | 128k | 66tok/sest. | 2419 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.9 GB | 125k | 227tok/sest. | 14116 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 8.3 GB | 128k | 72tok/sest. | 2175 tok/s | chat, coding, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.4 GB | – | 27tok/sest. | 1563 tok/s | chat, coding |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 46.6 GB | – | 30tok/sest. | 3663 tok/s | chat, coding |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.3 GB | – | 12tok/sest. | 1207 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 38.8 GB | – | 44tok/sest. | 2090 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q2_K | offload | 44.8 GB | – | 10tok/sest. | 738 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 46.6 GB | – | 38tok/sest. | 4606 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 33.8 GB | – | 52tok/sest. | 5840 tok/s | chat, coding, agents, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 43.2 GB | – | 3tok/sest. | 215 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 92.0 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 74.9 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 73.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 60.5 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5070 Ti
- Memory
- 16 GB GDDR7
- Memory bus
- 256-bit
- Memory bandwidth
- 896 GB/s
- FP16 compute
- 88 TFLOPS
- Software
- CUDA
- Board power
- 300 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16