NVIDIA RTX A6000
48 GB · 768 GB/s · 300 W
In short
The NVIDIA RTX A6000 has 48 GB of GDDR6 memory with 768 GB/s of bandwidth, which sets how fast it generates text. At 8k context it runs 78 of the 125 open models we track fully in memory; the most capable is DeepSeek V4 Flash at UD-Q2_K_XL, at about 38 tok/s (estimated). We have no current price for the NVIDIA RTX A6000 in the US.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the US, 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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | fits | 92.0 GB | 39k69k with q8 cache | 38tok/sest. | 273 tok/s | chat, coding |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q3_K_XL | fits | 85.2 GB | 256k | 9tok/sest. | 140 tok/s | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | fits | 73.2 GB | 95k175k with q8 cache | 50tok/sest. | 616 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 28.8 GB | 256k | 16tok/sest. | 305 tok/s | chat |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q5_K_M | fits | 86.7 GB | 256k | 37tok/sest. | 806 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 256k | 16tok/sest. | 305 tok/s | chat |
| gpt-oss 120B OpenAI | MXFP4 | fits | 60.5 GB | 128k | 83tok/sest. | 1367 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q8_0 | fits | 80.4 GB | 256k | 65tok/sest. | 2036 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | Q5_K_M | fits | 91.3 GB | 256k | 30tok/sest. | 710 tok/s | chat, coding, long documents |
| Gemma 4 31B | Q8_0 | fits | 32.9 GB | 256k | 14tok/sest. | 266 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q6_K | fits | 93.9 GB | 39k62k with q8 cache | 47tok/sest. | 1053 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.7 GB | 256k | 86tok/sest. | 2611 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 256k | 16tok/sest. | 305 tok/s | chat |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.5 GB | 256k | 63tok/sest. | 1990 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q6_K | fits | 94.8 GB | 8k14k with q8 cache | 20tok/sest. | 480 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.7 GB | 256k | 86tok/sest. | 2611 tok/s | chat, coding, agents, long documents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q8_0 | fits | 80.4 GB | 256k | 84tok/sest. | 2560 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 31.2 GB | 198k | 50tok/sest. | 1461 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 384k | 18tok/sest. | 344 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 33.8 GB | 256k | 83tok/sest. | 2721 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.6 GB | 128k | 109tok/sest. | 1890 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 49.9 GB | 1024k | 87tok/sest. | 2482 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 32.1 GB | 256k | 72tok/sest. | 1889 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 35.6 GB | 40k | 13tok/sest. | 235 tok/s | – |
| Gemma 4 12B | Q8_0 | fits | 13.4 GB | 256k | 36tok/sest. | 693 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.3 GB | 256k | 48tok/sest. | 878 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 18tok/sest. | 344 tok/s | chat |
| Gemma 3 27B | Q8_0 | fits | 28.9 GB | 128k | 16tok/sest. | 309 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 35.6 GB | 128k | 13tok/sest. | 246 tok/s | – |
| Llama 3.3 70B Meta | Q8_0 | fits | 73.5 GB | 74k128k with q8 cache | 6tok/sest. | 115 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 15.8 GB | 256k | 30tok/sest. | 570 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 17.0 GB | 40k | 28tok/sest. | 530 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.4 GB | 128k | 48tok/sest. | 927 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.4 GB | 40k | 48tok/sest. | 927 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 17.2 GB | 16k | 28tok/sest. | 533 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.6 GB | 256k | 99tok/sest. | 1767 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.6 GB | 256k | 47tok/sest. | 866 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.1 GB | 128k | 45tok/sest. | 860 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 9.0 GB | 128k | 56tok/sest. | 1064 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.9 GB | 125k | 195tok/sest. | 6210 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 8.3 GB | 128k | 62tok/sest. | 957 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.7 GB | 32k | 754tok/sest. | 12996 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 511tok/sest. | 8941 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 306tok/sest. | 3668 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.1 GB | 128k | 224tok/sest. | 4090 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.0 GB | 128k | 157tok/sest. | 2704 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 4.3 GB | 128k | 141tok/sest. | 2721 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 4.3 GB | 32k | 141tok/sest. | 2402 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 4.3 GB | 1024k | 140tok/sest. | 1924 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 5.1 GB | 128k | 111tok/sest. | 1801 tok/s | chat, coding, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.4 GB | 256k | 105tok/sest. | 1845 tok/s | chat, coding, agents, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 5.4 GB | 128k | 104tok/sest. | 1936 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 25.5 GB | 128k | 102tok/sest. | 3261 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.3 GB | 128k | 101tok/sest. | 2992 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.7 GB | 256k | 96tok/sest. | 1767 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 17.2 GB | 128k | 85tok/sest. | 2522 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 18.0 GB | 128k | 81tok/sest. | 2522 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 9.1 GB | 128k | 56tok/sest. | 1032 tok/s | chat, coding, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 9.1 GB | 32k | 56tok/sest. | 811 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 10.1 GB | 128k | 50tok/sest. | 957 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.6 GB | 256k | 47tok/sest. | 866 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 10.8 GB | 128k | 46tok/sest. | 749 tok/s | chat, coding, agents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 12.4 GB | 64k | 39tok/sest. | 749 tok/s | chat, coding |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 15.8 GB | 256k | 30tok/sest. | 570 tok/s | chat, coding |
| GLM 4.5V Z.ai | Q4_K_M | fits | 61.8 GB | 64k | 29tok/sest. | 461 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 17.3 GB | 128k | 28tok/sest. | 519 tok/s | chat, coding |
| GLM 4.6V Z.ai | Q4_K_M | fits | 68.2 GB | 128k | 26tok/sest. | 461 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 21.0 GB | 256k | 22tok/sest. | 305 tok/s | chat, coding |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 18tok/sest. | 350 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 25.7 GB | 40k | 18tok/sest. | 350 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 25.7 GB | 40k | 18tok/sest. | 350 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 18tok/sest. | 344 tok/s | chat |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 31.4 GB | 128k | 15tok/sest. | 282 tok/s | – |
| granite 4.2 30b IBM | Q8_0 | fits | 32.1 GB | 128k | 14tok/sest. | 277 tok/s | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q8_0 | fits | 73.5 GB | 74k128k with q8 cache | 6tok/sest. | 115 tok/s | – |
| Kimi Dev 72B Moonshot AI | Q8_0 | fits | 75.6 GB | 68k126k with q8 cache | 6tok/sest. | 112 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q5_K_M | fits | 86.1 GB | 32k60k with q8 cache | 5tok/sest. | 65 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q5_K_M | fits | 86.1 GB | 32k60k with q8 cache | 5tok/sest. | 64 tok/s | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | offload | 102.6 GB | – | 20tok/sest. | 264 tok/s | chat |
| MiniMax M2.5 MiniMax | MXFP4 | offload | 118.4 GB | – | 14tok/sest. | 541 tok/s | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 156.2 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.8 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 384.2 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.8 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.7 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 748.2 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.8 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.8 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- RTX A6000
- Memory
- 48 GB GDDR6
- Memory bus
- 384-bit
- Memory bandwidth
- 768 GB/s
- FP16 compute
- 38.71 TFLOPS
- Software
- CUDA
- Board power
- 300 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA RTX A6000 have for AI models?
- The NVIDIA RTX A6000 has 48 GB of GDDR6 memory with 768 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA RTX A6000 can run locally?
- DeepSeek V4 Flash (UD-Q2_K_XL) fits fully in its memory at 8k context and generates at about 38 tok/s, an estimate from its memory bandwidth. 78 of the 125 models we track fit at that context.
- Can the NVIDIA RTX A6000 run GLM 5.3 Flash?
- Not fully in memory: at UD-Q2_K_XL and 8k context GLM 5.3 Flash needs about 103 GB, so part of it runs from system RAM and it slows to about 20 tok/s (estimated).
- How much does the NVIDIA RTX A6000 cost in the US?
- We have no current price for the NVIDIA RTX A6000 in the US.
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.