NVIDIA · Ampere

What runs on a RTX A6000

48 GB at 768 GB/s. The largest model that fits at Q4_K_M is Llama 3.1 70B, at roughly 11.6 tokens per second.

Runs comfortably

6.4 GB of 44.3 GB · 15%
044 GB
Weights 4.6 GB
KV cache 1.0 GB
Runtime overhead 0.8 GB

Llama 3.1 8B at Q4_K_M leaves 37.9 GB spare on a RTX A6000. There is room to raise the context length or move up a quantisation level.

Generation92.3tok/s
Prompt processing1961tok/s
Max context128Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a RTX A6000

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 15.0 GB 16.8 GB Runs comfortably 128K 30.9
INT8 / W8A8 8.50 7.7 GB 9.5 GB Runs comfortably 128K 57.9
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Runs comfortably 128K 57.9
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Runs comfortably 128K 59.6
Q6_K 6.56 6.1 GB 8.0 GB Runs comfortably 128K 71.5
AWQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 128K 80.1
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 128K 80.1
MXFP4 4.25 5.4 GB 7.2 GB Runs comfortably 128K 80.1
Q5_K_M 5.67 5.3 GB 7.1 GB Runs comfortably 128K 81.6
Q5_K_S 5.52 5.2 GB 7.0 GB Runs comfortably 128K 83.6
Q4_K_M 4.85 4.6 GB 6.4 GB Runs comfortably 128K 92.3
Q4_K_S 4.58 4.4 GB 6.2 GB Runs comfortably 128K 96.4
Q4_0 4.55 4.4 GB 6.2 GB Runs comfortably 128K 96.9
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 128K 102
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 128K 108
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 128K 113
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 128K 128
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 128K 141
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 128K 164
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 128K 179

Models on a RTX A6000

Q4_K_M at 8K context. Bandwidth sets the speed; capacity sets the ceiling.

ModelParamsWeightsVerdictMax ctxtok/s
DeepSeek-R1 671B-A37B 671B 379.0 GB Won't fit 2.05
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 4.05
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 28.6
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 9.64
Qwen2.5 72B 72.7B 41.2 GB Won't fit 7K 9.90
Llama 3.1 70B 70.5B 40.0 GB Fits, but tight 11K 11.6
Mixtral 8x7B 46.7B 26.4 GB Runs comfortably 32K 51.2
Command R 35B 35.0B 20.1 GB Runs comfortably 19K 19.1
Yi-1.5 34B 34.4B 19.5 GB Runs comfortably 32K 23.3
Qwen3 32B 32.8B 18.6 GB Runs comfortably 99K 24.3
Qwen2.5-Coder 32B 32.8B 18.6 GB Runs comfortably 99K 24.3
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Runs comfortably 99K 24.3
Qwen3 30B-A3B 30.5B 17.3 GB Runs comfortably 128K 105
Gemma 3 27B 27.4B 15.6 GB Runs comfortably 128K 29.1
Mistral Small 24B 23.6B 13.4 GB Runs comfortably 32K 34.0
gpt-oss 20B-A3.6B 20.9B 11.9 GB Runs comfortably 128K 156
Qwen3 14B 14.8B 8.5 GB Runs comfortably 128K 52.3
Phi-4 14B 14.7B 8.4 GB Runs comfortably 16K 51.8
Mistral NeMo 12B 12.3B 7.0 GB Runs comfortably 128K 62.0
Gemma 3 12B 12.2B 7.0 GB Runs comfortably 128K 62.7
GLM-4 9B 9.4B 5.4 GB Runs comfortably 128K 84.7
Qwen3 8B 8.2B 4.7 GB Runs comfortably 128K 89.3
Llama 3.1 8B 8.0B 4.6 GB Runs comfortably 128K 92.3
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Runs comfortably 128K 92.3
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 128K 103
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 32K 102
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 173
Qwen3 4B 4.0B 2.3 GB Runs comfortably 128K 162
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 128K 204
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 539

Direct answers