gpu optimized

Best Local AI Models for RTX 4070 SUPER (12GB)

The RTX 4070 SUPER improves on the base 4070 with more CUDA cores. At 56 tokens per second, it delivers faster inference while maintaining the 12GB VRAM capacity for efficient 7B-9B models.

Specifications
VRAM
12 GB GDDR6X
Speed (8B Q4)
56 tok/s
Price
$759
Architecture
Ada Lovelace
Bandwidth
504 GB/s
Max Model Size
Up to 9B parameter models
Compatibility
10 excellent, 0 workable

RTX 4070 SUPER VRAM for AI: What Actually Fits?

Same 12GB GDDR6X and 504 GB/s bandwidth as the base RTX 4070, but extra CUDA cores push compute throughput higher. The result is 56 tok/s vs 52 tok/s — a modest but consistent improvement. VRAM usage is identical to other 12GB cards. Best for users who want peak speed with 7B-9B models and found a good deal on the SUPER variant.

RTX 4070 SUPER vs Similar GPUs

GPUVRAMSpeedBandwidthPrice
RTX 407012 GB52 tok/s504 GB/s$579
RTX 507012 GB59 tok/s672 GB/s$579
RTX 4070 SUPER12 GB56 tok/s504 GB/s$759
RTX 4070 Ti SUPER16 GB72 tok/s672 GB/s$1,148

Recommended Models

10 models
01

Qwen3.5 4B Instruct

Qwen / 4B / Q4_K_M / ~3.5 GB

Best for: Coding, Agents, Multimodal·Pop: 88/100

Perf: ~100.9 tok/s · first token ~0.3s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for coding, agents, multimodal on RTX 4070 SUPER.

ollama
ollama run qwen3.5:4b-instruct-q4_K_M
02

Llama 3.1 8B Instruct

Llama / 8B / Q4_K_M / ~6.5 GB

Best for: Chat, Coding·Pop: 94/100

Perf: ~56.0 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for chat, coding on RTX 4070 SUPER.

ollama
ollama run llama3.1:8b-instruct-q4_K_M
03

Qwen3.5 9B Instruct

Qwen / 9B / Q4_K_M / ~7 GB

Best for: Quality, Coding, Reasoning·Pop: 86/100

Perf: ~50.7 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for quality, coding, reasoning on RTX 4070 SUPER.

ollama
ollama run qwen3.5:9b-instruct-q4_K_M
04

Qwen3 8B

Qwen / 8B / Q4_K_M / ~6.5 GB

Best for: Chat, Coding·Pop: 88/100

Perf: ~56.0 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for chat, coding on RTX 4070 SUPER.

ollama
ollama run qwen3:8b-q4_K_M
05

Mistral 7B Instruct

Mistral / 7B / Q4_K_M / ~5.5 GB

Best for: Chat, Coding·Pop: 90/100

Perf: ~62.7 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for chat, coding on RTX 4070 SUPER.

ollama
ollama run mistral:7b-instruct-q4_K_M
06

Qwen2.5 Coder 7B

Qwen / 7B / Q4_K_M / ~5.5 GB

Best for: Coding·Pop: 85/100

Perf: ~62.7 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for coding on RTX 4070 SUPER.

ollama
ollama run qwen2.5-coder:7b-q4_K_M
07

Qwen2.5 7B Instruct

Qwen / 7B / Q4_K_M / ~5.5 GB

Best for: Chat, Coding·Pop: 86/100

Perf: ~62.7 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for chat, coding on RTX 4070 SUPER.

ollama
ollama run qwen2.5:7b-instruct-q4_K_M
08

LFM2 8B-A1B Instruct

LFM2 / 8B / Q4_K_M / ~6 GB

Best for: Local agents, tool calling, fast chat·Pop: 75/100

Perf: ~56.0 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for local agents, tool calling, fast chat on RTX 4070 SUPER.

ollama
ollama run liquidai/lfm2:8b-a1b-instruct-q4_K_M
09

DeepSeek-R1 Distill Qwen 7B

DeepSeek / 7B / Q4_K_M / ~5.5 GB

Best for: Reasoning, Coding·Pop: 77/100

Perf: ~62.7 tok/s · first token ~0.4s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for reasoning, coding on RTX 4070 SUPER.

ollama
ollama run deepseek-r1-distill:qwen-7b-q4_K_M
10

Gemma 3 4B Instruct

Gemma / 4B / Q4_K_M / ~3.5 GB

Best for: Chat, Coding·Pop: 81/100

Perf: ~100.9 tok/s · first token ~0.3s

Local OK//Excellent

Fits in 12 GB VRAM with room to spare. Best for chat, coding on RTX 4070 SUPER.

ollama
ollama run gemma3:4b-instruct-q4_K_M

Similar GPUs for Local AI

Compatible Model Families

RTX 4070 SUPER FAQ: Common Questions

How much VRAM does the RTX 4070 SUPER have for LLMs?

The RTX 4070 SUPER has 12GB GDDR6X VRAM, identical to the base RTX 4070. Both share 504 GB/s bandwidth. The SUPER variant adds more CUDA cores for faster compute, resulting in 56 tok/s vs 52 tok/s.

What size LLM can I run on an RTX 4070 SUPER?

Up to 9B parameter models at Q4 quantization. Same model capacity as the base 4070 and RTX 3060. The advantage is purely speed — 56 tok/s is 8% faster than the base 4070.

Is the RTX 4070 SUPER worth it over the base 4070 for AI?

At MSRP, the 4070 SUPER costs $180 more for an 8% speed boost. That is a poor value for AI workloads. Buy it only if the price gap is under $100, or if you also use the GPU for gaming.

RTX 4070 SUPER vs RTX 5070 for local LLMs?

The RTX 5070 is faster (59 vs 56 tok/s) and cheaper ($579 vs $759 MSRP). Both have 12GB VRAM. The 5070 wins on both price and performance for AI workloads.

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