NVIDIA · Ada

What runs on a RTX 4070

12 GB at 504 GB/s. The largest model that fits at Q4_K_M is Mistral NeMo 12B, at roughly 39.2 tokens per second.

Runs comfortably

6.4 GB of 10.5 GB · 61%
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 4.0 GB spare on a RTX 4070. There is room to raise the context length or move up a quantisation level.

Generation58.4tok/s
Prompt processing1517tok/s
Max context40Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a RTX 4070

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 4.86
INT8 / W8A8 8.50 7.7 GB 9.5 GB Fits, but tight 16K 36.6
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Fits, but tight 16K 36.6
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Runs comfortably 17K 37.6
Q6_K 6.56 6.1 GB 8.0 GB Runs comfortably 28K 45.2
AWQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 34K 50.6
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Runs comfortably 34K 50.6
MXFP4 4.25 5.4 GB 7.2 GB Runs comfortably 34K 50.6
Q5_K_M 5.67 5.3 GB 7.1 GB Runs comfortably 35K 51.6
Q5_K_S 5.52 5.2 GB 7.0 GB Runs comfortably 36K 52.9
Q4_K_M 4.85 4.6 GB 6.4 GB Runs comfortably 40K 58.4
Q4_K_S 4.58 4.4 GB 6.2 GB Runs comfortably 42K 61.0
Q4_0 4.55 4.4 GB 6.2 GB Runs comfortably 42K 61.3
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 44K 64.5
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 46K 68.6
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 48K 71.3
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 52K 81.3
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 55K 89.7
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 59K 104
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 61K 114

Models on a RTX 4070

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 1.82
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 2.96
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 13.1
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 4.12
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 1.09
Mixtral 8x7B 46.7B 26.4 GB Won't fit 6.67
Command R 35B 35.0B 20.1 GB Won't fit 1.53
Yi-1.5 34B 34.4B 19.5 GB Won't fit 2.81
Qwen3 32B 32.8B 18.6 GB Won't fit 3.02
Qwen2.5-Coder 32B 32.8B 18.6 GB Won't fit 3.02
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Won't fit 3.02
Qwen3 30B-A3B 30.5B 17.3 GB Won't fit 26.3
Gemma 3 27B 27.4B 15.6 GB Won't fit 4.49
Mistral Small 24B 23.6B 13.4 GB Won't fit 6.00
gpt-oss 20B-A3.6B 20.9B 11.9 GB Won't fit 45.3
Qwen3 14B 14.8B 8.5 GB Won't fit 8K 28.2
Phi-4 14B 14.7B 8.4 GB Won't fit 6K 24.4
Mistral NeMo 12B 12.3B 7.0 GB Runs comfortably 17K 39.2
Gemma 3 12B 12.2B 7.0 GB Runs comfortably 38K 39.7
GLM-4 9B 9.4B 5.4 GB Runs comfortably 109K 53.7
Qwen3 8B 8.2B 4.7 GB Runs comfortably 35K 56.5
Llama 3.1 8B 8.0B 4.6 GB Runs comfortably 40K 58.4
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Runs comfortably 40K 58.4
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 97K 64.9
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 32K 64.7
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 110
Qwen3 4B 4.0B 2.3 GB Runs comfortably 53K 103
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 72K 130
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 346

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