NVIDIA · Turing

What runs on a Tesla T4

16 GB at 320 GB/s. The largest model that fits at Q4_K_M is gpt-oss 20B-A3.6B, at roughly 70.1 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 Tesla T4. There is room to raise the context length or move up a quantisation level.

Generation38.1tok/s
Prompt processing1700tok/s
Max context70Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a Tesla T4

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 7.23
INT8 / W8A8 8.50 7.7 GB 9.5 GB Runs comfortably 46K 23.8
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Runs comfortably 46K 23.8
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Runs comfortably 48K 24.5
Q6_K 6.56 6.1 GB 8.0 GB Runs comfortably 58K 29.4
AWQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 64K 33.0
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 64K 33.0
MXFP4 4.25 5.4 GB 7.2 GB Runs comfortably 64K 33.0
Q5_K_M 5.67 5.3 GB 7.1 GB Runs comfortably 65K 33.6
Q5_K_S 5.52 5.2 GB 7.0 GB Runs comfortably 66K 34.4
Q4_K_M 4.85 4.6 GB 6.4 GB Runs comfortably 70K 38.1
Q4_K_S 4.58 4.4 GB 6.2 GB Runs comfortably 72K 39.8
Q4_0 4.55 4.4 GB 6.2 GB Runs comfortably 72K 40.0
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 74K 42.0
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 77K 44.7
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 78K 46.5
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 82K 53.0
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 85K 58.6
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 89K 68.0
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 91K 74.5

Models on a Tesla T4

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 1.88
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 3.08
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 14.2
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 4.40
Qwen2.5 72B 72.7B 41.2 GB Won't fit 1.16
Llama 3.1 70B 70.5B 40.0 GB Won't fit 1.20
Mixtral 8x7B 46.7B 26.4 GB Won't fit 7.81
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 3.59
Qwen3 32B 32.8B 18.6 GB Won't fit 3.89
Qwen2.5-Coder 32B 32.8B 18.6 GB Won't fit 3.89
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Won't fit 3.89
Qwen3 30B-A3B 30.5B 17.3 GB Won't fit 33.8
Gemma 3 27B 27.4B 15.6 GB Won't fit 6.29
Mistral Small 24B 23.6B 13.4 GB Won't fit 9.95
gpt-oss 20B-A3.6B 20.9B 11.9 GB Fits, but tight 33K 70.1
Qwen3 14B 14.8B 8.5 GB Runs comfortably 32K 21.5
Phi-4 14B 14.7B 8.4 GB Runs comfortably 16K 21.3
Mistral NeMo 12B 12.3B 7.0 GB Runs comfortably 41K 25.5
Gemma 3 12B 12.2B 7.0 GB Runs comfortably 98K 25.9
GLM-4 9B 9.4B 5.4 GB Runs comfortably 128K 35.0
Qwen3 8B 8.2B 4.7 GB Runs comfortably 62K 36.8
Llama 3.1 8B 8.0B 4.6 GB Runs comfortably 70K 38.1
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Runs comfortably 70K 38.1
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 128K 42.3
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 32K 42.2
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 72.0
Qwen3 4B 4.0B 2.3 GB Runs comfortably 79K 67.5
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 106K 84.8
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 227

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