NVIDIA · Turing

What runs on a RTX 2080 Ti

11 GB at 616 GB/s. The largest model that fits at Q4_K_M is Mistral NeMo 12B, at roughly 48.8 tokens per second.

Runs comfortably

6.4 GB of 9.5 GB · 67%
010 GB
Weights 4.6 GB
KV cache 1.0 GB
Runtime overhead 0.8 GB

Llama 3.1 8B at Q4_K_M leaves 3.1 GB spare on a RTX 2080 Ti. There is room to raise the context length or move up a quantisation level.

Generation72.8tok/s
Prompt processing706tok/s
Max context33Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a RTX 2080 Ti

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 4.58
INT8 / W8A8 8.50 7.7 GB 9.5 GB Fits, but tight 8K 45.6
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Fits, but tight 8K 45.6
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Fits, but tight 10K 46.9
Q6_K 6.56 6.1 GB 8.0 GB Runs comfortably 21K 56.3
AWQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 26K 63.1
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 26K 63.1
MXFP4 4.25 5.4 GB 7.2 GB Runs comfortably 26K 63.1
Q5_K_M 5.67 5.3 GB 7.1 GB Runs comfortably 27K 64.3
Q5_K_S 5.52 5.2 GB 7.0 GB Runs comfortably 28K 65.8
Q4_K_M 4.85 4.6 GB 6.4 GB Runs comfortably 33K 72.8
Q4_K_S 4.58 4.4 GB 6.2 GB Runs comfortably 35K 76.0
Q4_0 4.55 4.4 GB 6.2 GB Runs comfortably 35K 76.4
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 37K 80.3
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 39K 85.4
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 40K 88.8
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 44K 101
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 47K 112
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 51K 129
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 53K 142

Models on a RTX 2080 Ti

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 1.86
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 3.02
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 13.4
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 4.14
Qwen2.5 72B 72.7B 41.2 GB Won't fit 1.05
Llama 3.1 70B 70.5B 40.0 GB Won't fit 1.10
Mixtral 8x7B 46.7B 26.4 GB Won't fit 6.64
Command R 35B 35.0B 20.1 GB Won't fit 1.56
Yi-1.5 34B 34.4B 19.5 GB Won't fit 2.73
Qwen3 32B 32.8B 18.6 GB Won't fit 2.94
Qwen2.5-Coder 32B 32.8B 18.6 GB Won't fit 2.94
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Won't fit 2.94
Qwen3 30B-A3B 30.5B 17.3 GB Won't fit 25.9
Gemma 3 27B 27.4B 15.6 GB Won't fit 4.23
Mistral Small 24B 23.6B 13.4 GB Won't fit 5.49
gpt-oss 20B-A3.6B 20.9B 11.9 GB Won't fit 40.6
Qwen3 14B 14.8B 8.5 GB Won't fit 2K 19.9
Phi-4 14B 14.7B 8.4 GB Won't fit 2K 17.9
Mistral NeMo 12B 12.3B 7.0 GB Fits, but tight 11K 48.8
Gemma 3 12B 12.2B 7.0 GB Fits, but tight 23K 49.4
GLM-4 9B 9.4B 5.4 GB Runs comfortably 85K 66.8
Qwen3 8B 8.2B 4.7 GB Runs comfortably 28K 70.4
Llama 3.1 8B 8.0B 4.6 GB Runs comfortably 33K 72.8
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Runs comfortably 33K 72.8
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 79K 80.9
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 32K 80.6
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 137
Qwen3 4B 4.0B 2.3 GB Runs comfortably 46K 128
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 63K 161
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 428

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