12GB VRAM

RTX 5070 — what LLMs can it run?

46 of 81 indexed models fit comfortably in 12GB at 4K context, each at the highest-quality quant that still leaves headroom.

14B · 16

RTX 5070 — what LLMs can it run? — 14B
Model	Quant	Est. VRAM	Headroom	tok/s
DeepSeek-Coder-V2-Lite Instruct16B	AWQ INT4	9.13 GB	+2.9 GB	192
DeepSeek-V2-Lite Chat16B	AWQ INT4	9.13 GB	+2.9 GB	188
StarCoder2 15B15B	Q4_K_M	10.19 GB	+1.8 GB	92
Qwen3 14B Instruct14B	EXL2 4.65bpw	9.66 GB	+2.3 GB	125
Qwen2.5 14B Instruct14B	EXL2 4.65bpw	9.75 GB	+2.3 GB	138
DeepSeek-R1-Distill-Qwen-14B14B	EXL2 4.65bpw	9.75 GB	+2.3 GB	128
Phi-4 14B14B	Q4_K_M	10.17 GB	+1.8 GB	88
Phi-3 Medium 14B Instruct14B	Q4_K_M	9.73 GB	+2.3 GB	102
Mistral Nemo 12B Instruct12B	Q4_K_M	8.42 GB	+3.6 GB	112
Gemma 3 12B IT12B	Q4_K_M	9.28 GB	+2.7 GB	105
Stable LM 2 12B Chat12B	Q4_K_M	8.35 GB	+3.7 GB	108
Jamba 1.5 Mini12B	Q4_K_M	8.15 GB	+3.9 GB	95
Llama 3.2 11B Vision Instruct11B	Q4_K_M	7.66 GB	+4.3 GB	88
Solar 10.7B Instruct11B	Q4_K_M	7.6 GB	+4.4 GB	125
Falcon 3 10B Instruct10B	Q4_K_M	7.28 GB	+4.7 GB	118
Gemma 2 9B Instruct9B	Q4_K_M	7.3 GB	+4.7 GB	132

7B · 20

RTX 5070 — what LLMs can it run? — 7B
Model	Quant	Est. VRAM	Headroom	tok/s
GLM-4-9B-Chat9B	Q8_0	10.16 GB	+1.8 GB	105
Qwen3-VL 8B Instruct8B	Q8_0	10.39 GB	+1.6 GB	108
Ministral 3 8B Instruct8B	Q8_0	10.02 GB	+2 GB	—
Qwen2-VL 7B Instruct7B	Q4_K_M	5.49 GB	+6.5 GB	72
Granite 3.1 8B Instruct8B	Q4_K_M	5.88 GB	+6.1 GB	142
Qwen3 8B Instruct8B	Q6_K	7.64 GB	+4.4 GB	122
Llama 3.1 8B Instruct8B	Q8_0	9.47 GB	+2.5 GB	118
Nous Hermes 3 Llama 3.1 8B8B	EXL2 4.65bpw	5.43 GB	+6.6 GB	232
Aya 23 8B8B	Q4_K_M	5.64 GB	+6.4 GB	145
OpenChat 3.6 8B8B	EXL2 4.65bpw	5.43 GB	+6.6 GB	228
DeepSeek-R1-Distill-Llama-8B8B	Q5_K_M	6.51 GB	+5.5 GB	128
InternLM2 7B Chat7B	Q4_K_M	5.45 GB	+6.6 GB	148
Qwen2.5 7B Instruct7B	Q6_K	6.77 GB	+5.2 GB	132
Qwen2.5-Coder 7B Instruct7B	EXL2 4.65bpw	4.87 GB	+7.1 GB	248
WizardLM-2 7B7B	Q4_K_M	5.07 GB	+6.9 GB	152
DeepSeek-R1-Distill-Qwen-7B7B	EXL2 4.65bpw	4.87 GB	+7.1 GB	210
OLMo 2 7B Instruct7B	Q8_0	10.3 GB	+1.7 GB	125
Mistral 7B Instruct v0.37B	Q6_K	6.75 GB	+5.3 GB	135
Zephyr 7B Beta7B	Q6_K	6.75 GB	+5.3 GB	132
Gemma 3 4B IT4B	Q8_0	5.36 GB	+6.6 GB	145

≤3B · 10

RTX 5070 — what LLMs can it run? — ≤3B
Model	Quant	Est. VRAM	Headroom	tok/s
Qwen3 4B Instruct4B	Q6_K	4.05 GB	+8 GB	145
Phi-4 Mini Instruct3.8B	Q8_0	4.68 GB	+7.3 GB	262
Phi-3.5 Mini Instruct3.8B	Q8_0	5.89 GB	+6.1 GB	255
Llama 3.2 3B Instruct3B	Q8_0	4.05 GB	+8 GB	285
Qwen2.5 3B Instruct3B	Q8_0	3.67 GB	+8.3 GB	290
Gemma 2 2B Instruct2B	Q8_0	3.34 GB	+8.7 GB	320
Qwen3 1.7B Instruct1.7B	Q8_0	2.39 GB	+9.6 GB	240
Qwen2.5 1.5B Instruct1.5B	Q8_0	1.83 GB	+10.2 GB	410
Llama 3.2 1B Instruct1B	Q8_0	1.51 GB	+10.5 GB	450
Qwen2.5 0.5B Instruct0.5B	Q8_0	0.6 GB	+11.4 GB	540

How this list is built

Each row is the lowest-perplexity-loss quant of that model whose estimated total — weights plus KV cache at 4K context plus activation buffer — uses at most 88% of the card. That is the calculator's "green" threshold, so every row here has real headroom rather than only just fitting. Raise the context length and the list shortens; the calculator lets you check any combination directly.

A further 2 models load but with no headroom to spare (up to 105% of VRAM) — the Quant Hub’s GPU chips count those too, which is why its number is higher.

Open this card in the VRAM calculator Browse all 81 models

Measured on this card

No benchmark runs in this index were recorded on a RTX 5070. Every figure on this page is calculated from the model architecture and the quant level — treat them as estimates, not measurements.

Cards with the same budget

What fits is decided by memory, so every 12GB card of this type returns the same list. These pages are not different answers — they differ in throughput, which this index does not measure per card.

Stepping up

A RTX 5080 (16GB) fits 6 more of the indexed models than this card. RTX 5080 →