NVIDIA GeForce RTX 5070

NVIDIA · 12GBGDDR7 · Can run 63 models

Manufacturer	NVIDIA
VRAM	12 GB
Memory Type	GDDR7
Architecture	Blackwell
CUDA Cores	6,144
Tensor Cores	192
Bandwidth	672 GB/s
TDP	250W
MSRP	$549
Released	Mar 10, 2025

AI Notes

The RTX 5070 brings next-gen GDDR7 memory with 672 GB/s bandwidth to the mid-range. With 12GB VRAM, it handles 7B models at very fast speeds and runs 13B models with quantization. The Blackwell architecture's efficiency improvements make it one of the best value cards for local AI.

Compatible Models

Model	Parameters	Best Quant	VRAM Used	Fit	Est. Speed
Qwen 3 0.6B	600M	Q4_K_M	2.5 GB	Runs	~269 tok/s
Qwen 3.5 0.8B	800M	Q4_K_M	1.5 GB	Runs	~448 tok/s
Gemma 3 1B	1B	Q8_0	2 GB	Runs	~336 tok/s
Llama 3.2 1B	1B	Q8_0	3 GB	Runs	~224 tok/s
DeepSeek R1 1.5B	1.5B	Q8_0	3 GB	Runs	~224 tok/s
SmolLM2 1.7B	1.7B	Q8_0	2.7 GB	Runs	~249 tok/s
Gemma 2 2B	2B	Q8_0	4 GB	Runs	~168 tok/s
Gemma 3n E2B	2B	Q4_K_M	3.3 GB	Runs	~204 tok/s
Gemma 4 E2B	2B	Q4_K_M	4 GB	Runs	~168 tok/s
Qwen 3.5 2B	2B	Q4_K_M	3 GB	Runs	~224 tok/s
Llama 3.2 3B	3B	Q8_0	5 GB	Runs	~134 tok/s
StarCoder2 3B	3B	Q4_K_M	3.5 GB	Runs	~192 tok/s
Phi-3 Mini 3.8B	3.8B	Q8_0	5.8 GB	Runs	~116 tok/s
Phi-4 Mini 3.8B	3.8B	Q4_K_M	4.5 GB	Runs	~149 tok/s
Gemma 3 4B	4B	Q4_K_M	5 GB	Runs	~134 tok/s
Gemma 3n E4B	4B	Q4_K_M	4.5 GB	Runs	~149 tok/s
Gemma 4 E4B	4B	Q4_K_M	6 GB	Runs	~112 tok/s
Qwen 3 4B	4B	Q4_K_M	4.5 GB	Runs	~149 tok/s
Qwen 3.5 4B	4B	Q4_K_M	4.5 GB	Runs	~149 tok/s
Yi 1.5 6B	6B	Q4_K_M	5 GB	Runs	~134 tok/s
Codestral Mamba 7B	7B	Q4_K_M	6.9 GB	Runs	~97 tok/s
DeepSeek R1 7B	7B	Q8_0	9 GB	Runs	~75 tok/s
Falcon 3 7B	7B	Q4_K_M	6.8 GB	Runs	~99 tok/s
InternLM 2.5 7B	7B	Q4_K_M	5.5 GB	Runs	~122 tok/s
Mistral 7B	7B	Q8_0	9 GB	Runs	~75 tok/s
OpenChat 3.5 7B	7B	Q4_K_M	6.9 GB	Runs	~97 tok/s
Qwen 2.5 7B	7B	Q8_0	9 GB	Runs	~75 tok/s
Qwen 2.5 Coder 7B	7B	Q8_0	9 GB	Runs	~75 tok/s
Qwen 2.5 VL 7B	7B	Q4_K_M	7 GB	Runs	~96 tok/s
StarCoder2 7B	7B	Q4_K_M	5.5 GB	Runs	~122 tok/s
WizardLM 2 7B	7B	Q4_K_M	6.9 GB	Runs	~97 tok/s
Aya Expanse 8B	8B	Q4_K_M	6.5 GB	Runs	~103 tok/s
Cogito 8B	8B	Q4_K_M	7.5 GB	Runs	~90 tok/s
DeepSeek R1 8B	8B	Q4_K_M	7.5 GB	Runs	~90 tok/s
Dolphin 3 8B	8B	Q4_K_M	6 GB	Runs	~112 tok/s
Granite 3.3 8B	8B	Q8_0	10 GB	Runs	~67 tok/s
Llama 3.1 8B	8B	Q8_0	10 GB	Runs	~67 tok/s
Nemotron 3 Nano 8B	8B	Q4_K_M	7.5 GB	Runs	~90 tok/s
Nous Hermes 2 8B	8B	Q4_K_M	6 GB	Runs	~112 tok/s
Qwen 3 8B	8B	Q4_K_M	7.5 GB	Runs	~90 tok/s
Qwen 3.5 9B	9B	Q4_K_M	7.5 GB	Runs	~90 tok/s
Yi 1.5 9B	9B	Q4_K_M	6.5 GB	Runs	~103 tok/s
Yi Coder 9B	9B	Q4_K_M	8 GB	Runs	~84 tok/s
Falcon 3 10B	10B	Q4_K_M	8.5 GB	Runs	~79 tok/s
Llama 3.2 Vision 11B	11B	Q4_K_M	8.5 GB	Runs	~79 tok/s
Mistral Nemo 12B	12B	Q4_K_M	9.5 GB	Runs	~71 tok/s
DeepSeek R1 14B	14B	Q4_K_M	9.9 GB	Runs	~68 tok/s
Phi-4 14B	14B	Q4_K_M	9.9 GB	Runs	~68 tok/s
Qwen 2.5 14B	14B	Q4_K_M	9.9 GB	Runs	~68 tok/s
Gemma 2 9B	9B	Q8_0	11 GB	Runs (tight)	~61 tok/s
Gemma 3 12B	12B	Q4_K_M	10.5 GB	Runs (tight)	~64 tok/s
Phi-4 Reasoning 14B	14B	Q4_K_M	11 GB	Runs (tight)	~61 tok/s
Qwen 2.5 Coder 14B	14B	Q4_K_M	12 GB	CPU Offload	~17 tok/s
Qwen 3 14B	14B	Q4_K_M	12 GB	CPU Offload	~17 tok/s
StarCoder2 15B	15B	Q8_0	17 GB	CPU Offload	~12 tok/s
InternLM 2.5 20B	20B	Q4_K_M	12 GB	CPU Offload	~17 tok/s
gpt-oss 20B	21B	MXFP4	15 GB	CPU Offload	~14 tok/s
Codestral 22B	22B	Q4_K_M	14.7 GB	CPU Offload	~14 tok/s
Devstral 24B	24B	Q4_K_M	17 GB	CPU Offload	~12 tok/s
Magistral Small 24B	24B	Q4_K_M	17 GB	CPU Offload	~12 tok/s
Mistral Small 3.1 24B	24B	Q4_K_M	18 GB	CPU Offload	~11 tok/s
Gemma 2 27B	27B	Q4_K_M	17.7 GB	CPU Offload	~11 tok/s
Qwen 3.5 35B A3B	35B	Q4_K_M	12 GB	CPU Offload	~17 tok/s

51 model(s) are too large for this hardware.