RTX 4070
60 AI models fit in 12 GB VRAM at Q4 native. 21 more run with CPU offloading. Real benchmarks below.
llama.cpp 0.2.x · CUDA 12 · Ubuntu 22.04 · Prices verified on Amazon · methodology →
Execution Context
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Full Specifications
NVIDIA · 2023-04
| VRAM | 12 GB GDDR6X |
| Bandwidth | 504 GB/s |
| FP16 TFLOPS | 29.1 |
| AI Score | 48 / 140 |
| CUDA Cores | 5,888 |
| Tensor Cores | 184 |
| TDP | 200 W |
| PCIe | Gen 4 |
| Slots | 2 |
| Power Connector | 16-pin |
| Price Band | Mittelklasse |
| Released | 2023-04 |
AI Benchmarks
Real inference measurements — llama.cpp Q4_K_M
| Task | Result |
|---|---|
| Llama 1B Q4 | 265 tok/s |
| Llama 3B Q4 | 106 tok/s |
| Llama 7B Q4 | 40 tok/s |
| Llama 13B Q4 | 20 tok/s |
| Llama 30B Q4 | VRAM N/A |
| Llama 70B Q4 | Offload or multi-GPU |
| Stable Diffusion 512px | 4.5s / img |
| Whisper Large RTF | 0.55x |
RTF < 1.0 = faster than real time. For Stable Diffusion and Whisper lower is better; for tokens/s higher is better.
Compare RTX 4070 with another GPU
Is an upgrade worth it? Compare specs and real benchmarks side by side.
Open comparator →Compatible AI Models — RTX 4070
60 models run fully in VRAM · 21 with CPU offloading
Flux.1 Dev
Whisper Large V3
Stable Diffusion 3.5 Large
Stable Diffusion 3.5 Medium
Phi-4
Stable Diffusion 3 Medium
Flux.1 Schnell
DeepSeek R1 Distill 14B
Show all 60 compatible models →
Also runs with CPU offloading (21)
- FLUX.2 Dev 8.8 GB Q2
- Qwen2.5-Coder 32B 9.6 GB Q2 How to install →
- DeepSeek R1 Distill 32B 9.6 GB Q2 How to install →
- Qwen2.5 32B 9.6 GB Q2 How to install →
- Gemma 4 27B 7.4 GB Q2 How to install →
- Qwen3.5 35B-A3B 9.6 GB Q2 How to install →
- Gemma 2 27B 8 GB Q2 How to install →
- Gemma 3 27B 8.1 GB Q2 How to install →
- Gemma 4 31B 8.5 GB Q2 How to install →
- Mistral Small 3 7.2 GB Q2 How to install →
- Qwen3 32B 8.8 GB Q2 How to install →
- Qwen3-Coder 30B-A3B 8.3 GB Q2 How to install →
- Qwen3 30B-A3B 8.3 GB Q2 How to install →
- Devstral Small 2 24B 6.6 GB Q2 How to install →
- Qwen3.5 27B 7.4 GB Q2 How to install →
- Magistral Small 24B 6.6 GB Q2 How to install →
- CodeLlama 34B 10 GB Q2 How to install →
- Yi 1.5 34B 10 GB Q2 How to install →
- Mistral Small 3.2 6.6 GB Q2 How to install →
- Mistral Small 3.1 6.6 GB Q2 How to install →
- Phi-3.5 MoE 11 GB Q2 How to install →
RTX 4070 · Amazon
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RTX 4070 for Local AI
La RTX 4070 con 12GB de GDDR6X es perfecta para empezar con IA local. Cubre todos los modelos 7B populares en Q4 (Llama 3.1 8B, Mistral 7B, Qwen2.5 7B, DeepSeek R1 Distill 8B) con velocidades decentes. Para casos de uso ligeros como chat, coding assistance y transcripción de audio, esta GPU tiene todo lo necesario.
En benchmarks reales, la RTX 4070 genera 40 tokens/segundo con Llama 7B Q4 — suficiente para conversación en tiempo real. Whisper para transcripción de voz funciona perfectamente. Para generación de imágenes, Stable Diffusion 3 Medium y SD 3.5 Medium son compatibles.
Si buscas tu primera GPU para IA local con un presupuesto ajustado, la RTX 4070 es un punto de entrada sólido. Consulta nuestra guía para empezar con IA local y usa la calculadora de VRAM para verificar la compatibilidad con tu modelo favorito.
Plan your full AI build
RTX 4070 · 12 GB VRAM — configure PSU, RAM, storage and check compatible models.
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