NVIDIA · Ada

What runs on a RTX 4080 Super

16 GB at 736 GB/s. The largest model that fits at Q4_K_M is gpt-oss 20B-A3.6B, at roughly 145 tokens per second.

Runs comfortably

6.4 GB of 14.2 GB · 45%
014 GB
Weights 4.6 GB
KV cache 1.0 GB
Runtime overhead 0.8 GB

Llama 3.1 8B at Q4_K_M leaves 7.8 GB spare on a RTX 4080 Super. There is room to raise the context length or move up a quantisation level.

Generation84.9tok/s
Prompt processing2720tok/s
Max context70Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a RTX 4080 Super

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 Won't fit 9.58
INT8 / W8A8 8.50 7.7 GB 9.5 GB Runs comfortably 46K 53.2
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Runs comfortably 46K 53.2
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Runs comfortably 48K 54.7
Q6_K 6.56 6.1 GB 8.0 GB Runs comfortably 58K 65.7
AWQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 64K 73.6
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 64K 73.6
MXFP4 4.25 5.4 GB 7.2 GB Runs comfortably 64K 73.6
Q5_K_M 5.67 5.3 GB 7.1 GB Runs comfortably 65K 75.0
Q5_K_S 5.52 5.2 GB 7.0 GB Runs comfortably 66K 76.8
Q4_K_M 4.85 4.6 GB 6.4 GB Runs comfortably 70K 84.9
Q4_K_S 4.58 4.4 GB 6.2 GB Runs comfortably 72K 88.6
Q4_0 4.55 4.4 GB 6.2 GB Runs comfortably 72K 89.1
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 74K 93.7
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 77K 99.5
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 78K 104
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 82K 118
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 85K 130
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 89K 151
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 91K 165

Models on a RTX 4080 Super

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 1.85
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 3.05
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 14.3
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 4.43
Qwen2.5 72B 72.7B 41.2 GB Won't fit 1.18
Llama 3.1 70B 70.5B 40.0 GB Won't fit 1.22
Mixtral 8x7B 46.7B 26.4 GB Won't fit 8.45
Command R 35B 35.0B 20.1 GB Won't fit 1.77
Yi-1.5 34B 34.4B 19.5 GB Won't fit 4.00
Qwen3 32B 32.8B 18.6 GB Won't fit 4.39
Qwen2.5-Coder 32B 32.8B 18.6 GB Won't fit 4.39
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Won't fit 4.39
Qwen3 30B-A3B 30.5B 17.3 GB Won't fit 40.9
Gemma 3 27B 27.4B 15.6 GB Won't fit 7.98
Mistral Small 24B 23.6B 13.4 GB Won't fit 15.3
gpt-oss 20B-A3.6B 20.9B 11.9 GB Fits, but tight 33K 145
Qwen3 14B 14.8B 8.5 GB Runs comfortably 32K 48.0
Phi-4 14B 14.7B 8.4 GB Runs comfortably 16K 47.6
Mistral NeMo 12B 12.3B 7.0 GB Runs comfortably 41K 57.0
Gemma 3 12B 12.2B 7.0 GB Runs comfortably 98K 57.7
GLM-4 9B 9.4B 5.4 GB Runs comfortably 128K 77.9
Qwen3 8B 8.2B 4.7 GB Runs comfortably 62K 82.1
Llama 3.1 8B 8.0B 4.6 GB Runs comfortably 70K 84.9
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Runs comfortably 70K 84.9
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 128K 94.4
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 32K 93.9
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 159
Qwen3 4B 4.0B 2.3 GB Runs comfortably 79K 149
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 106K 188
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 497

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