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RTX 4070 Ti

CPU bottleneck check, compatible CPUs, and AI models it can run

GeForce RTX 4070 Ti / NVIDIA made / RTX 40 / Released 2023 Also known as: RTX4070Ti / 4070Ti

Performance Score
28,000
VRAM
12GB
Power Draw (TDP)
285W
Manufacturer
NVIDIA
Type
Desktop

GeForce RTX 4070 Ti (NVIDIA, released in 2023, also listed as RTX4070Ti / 4070Ti) is a graphics card with a performance score of 28,000 and 12GB of VRAM, TDP 285W. If CPU compatibility and performance balance are poor, a CPU bottleneck occurs, preventing RTX 4070 Ti from reaching its full potential. In our estimate, the CPUs that pair best with RTX 4070 Ti are Intel: Core i7-13700K (estimated bottleneck: about 0%), and AMD: Ryzen 9 7950X3D (about 0%). Below are the top 10 compatible CPUs, CPUs to avoid, and generative AI models supported by this amount of VRAM.

Top 10 CPUs Compatible with GeForce RTX 4070 Ti

CPUs are ordered by proximity to the ideal CPU:GPU ratio of 0.9:1. A lower bottleneck percentage means more of the GPU’s performance can be used.

46,000 pts
Bottleneck 0%
45,500 pts
Bottleneck 0%
52,000 pts
Bottleneck 0%
51,500 pts
Bottleneck 0%
63,000 pts
Bottleneck 0%
58,000 pts
Bottleneck 0%
57,500 pts
Bottleneck 0%
55,000 pts
Bottleneck 0%
54,500 pts
Bottleneck 0%
60,000 pts
Bottleneck 0%
Check Compatibility with Your CPU →

The Bottleneck Checker opens with GeForce RTX 4070 Ti already selected.

RTX 4070 Ti and CPU Compatibility | Where Does a CPU Bottleneck Begin?

RTX 4070 Ti (RTX4070Ti / 4070Ti) has a performance score of 28,000 points. Using the same CPU:GPU ≈ 0.9:1 standard as the checker, compatibility by CPU score is shown below.

Example CPUs to PairRatingWhat It Means
Ryzen 9 9950X3D、Ryzen 9 9900X3D、Ryzen 7 9800X3D Great Match: 10% or Less Optimal balance. Nearly all of RTX 4070 Ti performance can be used
Core i5-13400F、Core i9-10900、Core i9-10900F Acceptable: 10–25% Practical with no major issue. Consider a future upgrade if targeting high fps.
Core i5-12400、Ryzen 9 3950X、Ryzen 9 3900XT CPU Too Weak: Over 25% A clear CPU bottleneck. Much of the GPU performance is wasted
— CPU Overkill Almost no desktop CPUs match this category because this GPU is already top-tier.

Note: Perceived results vary by resolution and game (GPU matters more at 4K, while CPU matters more at high-fps Full HD). For an exact estimate, use the Bottleneck Checker.

AI Models That Run on GeForce RTX 4070 Ti (VRAM 12GB)

Runs Comfortably: Meets recommended VRAM / Barely Runs: Meets minimum VRAM (lower quality or quantization may be needed)

Image generation

Comfortable
SD 1.5 (Q4 quantized)
Image generation
GGUF Q4_K_M, ultra-lightweight
Minimum 2GB / Recommended 4GB
Comfortable
Stable Diffusion 1.5
Image generation
Basic image generation
Minimum 4GB / Recommended 6GB
Comfortable
SDXL Turbo
Image generation
1-step real-time generation
Minimum 6GB / Recommended 8GB
Comfortable
SDXL Lightning
Image generation
Fast version, 2-8 steps
Minimum 6GB / Recommended 8GB
Comfortable
SDXL (Q4 quantized)
Image generation
GGUF Q4_K_M, low VRAM
Minimum 4GB / Recommended 6GB
Comfortable
SDXL (Q8 quantized)
Image generation
GGUF Q8_0, near full quality
Minimum 6GB / Recommended 8GB
Comfortable
Stable Diffusion XL
Image generation
High quality at 1024×1024
Minimum 8GB / Recommended 12GB
Comfortable
Pony Diffusion v6
Image generation
Specialized for anime and characters
Minimum 8GB / Recommended 12GB
Comfortable
Animagine XL
Image generation
Anime image generation
Minimum 8GB / Recommended 12GB
Comfortable
Flux.1 [schnell]
Image generation
4-step fast generation, commercial use allowed
Minimum 8GB / Recommended 12GB
Comfortable
Flux.1 [dev] (Q4)
Image generation
GGUF Q4, lighter weight
Minimum 8GB / Recommended 10GB
Comfortable
Flux.1 [dev] (Q5)
Image generation
GGUF Q5, balanced
Minimum 10GB / Recommended 12GB
Comfortable
IP-Adapter SDXL
Image generation
Generate from a reference image
Minimum 8GB / Recommended 12GB
Comfortable
Real-ESRGAN x4
Image generation
Image upscaling (4x)
Minimum 4GB / Recommended 6GB
Comfortable
Illustrious XL v2.0
Image generation
By OnomaAI, anime-focused SDXL-based model with many derivatives
Minimum 8GB / Recommended 12GB
Comfortable
Stable Diffusion 3.5 Medium
Image generation
By Stability AI, 2.5B, strong at rendering text
Minimum 10GB / Recommended 12GB
Comfortable
FLUX.1 [dev] (GGUF Q4)
Image generation
Q4_K_S, runs even on 8GB cards, non-commercial license
Minimum 7GB / Recommended 12GB
△ Barely
Flux.1 [dev] (Q8)
Image generation
GGUF Q8, near full quality
Minimum 12GB / Recommended 16GB
△ Barely
ControlNet + SDXL
Image generation
Pose, line art, and depth control
Minimum 10GB / Recommended 16GB
△ Barely
Stable Cascade
Image generation
Würstchen-based, fast
Minimum 12GB / Recommended 16GB
△ Barely
Kolors
Image generation
Made by Kuaishou, photorealistic
Minimum 12GB / Recommended 16GB
△ Barely
FLUX.1 Krea [dev] (FP8)
Image generation
BFL x Krea, photorealistic derivative of Flux dev, 12B
Minimum 12GB / Recommended 16GB
△ Barely
FLUX.2 [klein] 4B
Image generation
BFL, January 2026, generation and editing in one model, under 1 second, Apache 2.0
Minimum 12GB / Recommended 16GB
△ Barely
Qwen-Image (GGUF Q4)
Image generation
Alibaba, 20B quantized, for 12GB cards
Minimum 12GB / Recommended 16GB
△ Barely
HiDream-I1 (GGUF Q4)
Image generation
HiDream.ai, 17B, quantized version, MIT
Minimum 12GB / Recommended 16GB

Video generation

Comfortable
AnimateDiff (SD1.5)
Video generation
SD-based animation videos
Minimum 8GB / Recommended 12GB
Comfortable
Wan 2.1 T2V-1.3B
Video generation
Alibaba, official figure 8.19GB, short 480p videos
Minimum 8GB / Recommended 12GB
Comfortable
FramePack
Video generation
lllyasviel, 13B based on HunyuanVideo, memory use stays constant for long videos, uses a lot of system RAM
Minimum 8GB / Recommended 12GB
△ Barely
Stable Video Diffusion
Video generation
Short video generation (4 seconds)
Minimum 12GB / Recommended 16GB
△ Barely
AnimateDiff (SDXL)
Video generation
SDXL-based animation videos
Minimum 12GB / Recommended 20GB
△ Barely
CogVideoX-2B
Video generation
Open-source video generation
Minimum 12GB / Recommended 18GB
△ Barely
LTX-Video
Video generation
Lightricks, fast video generation
Minimum 12GB / Recommended 16GB
△ Barely
Wan 2.2 TI2V-5B
Video generation
Alibaba, 720p, runs in 8GB with ComfyUI automatic offloading, official script needs 24GB
Minimum 8GB / Recommended 16GB

Large language models (LLM)

Comfortable
Qwen 2.5 0.5B (Q4)
Large language models (LLM)
Lightest model, for embedded devices
Minimum 1GB / Recommended 2GB
Comfortable
Qwen 2.5 1.5B (Q4)
Large language models (LLM)
Ultra-lightweight, runs on phones
Minimum 2GB / Recommended 3GB
Comfortable
Phi-3 mini 3.8B (Q4)
Large language models (LLM)
Small, high-performance model by Microsoft
Minimum 3GB / Recommended 4GB
Comfortable
Gemma 3 4B (Q4)
Large language models (LLM)
Lightweight model by Google
Minimum 3GB / Recommended 4GB
Comfortable
Llama 3.2 3B (Q4)
Large language models (LLM)
Small mobile model by Meta
Minimum 3GB / Recommended 4GB
Comfortable
Llama 3.2 1B (Q4)
Large language models (LLM)
Smallest mobile model by Meta
Minimum 2GB / Recommended 3GB
Comfortable
Mistral 7B (Q2)
Large language models (LLM)
Extreme quantization, quality trade-off
Minimum 3GB / Recommended 4GB
Comfortable
Mistral 7B (Q4)
Large language models (LLM)
Efficient, recommended setting
Minimum 5GB / Recommended 6GB
Comfortable
Mistral 7B (Q5)
Large language models (LLM)
Balanced quantization
Minimum 6GB / Recommended 7GB
Comfortable
Mistral 7B (Q8)
Large language models (LLM)
High-quality quantization
Minimum 8GB / Recommended 10GB
Comfortable
Llama 3.1 8B (Q4)
Large language models (LLM)
Meta, standard for chat
Minimum 6GB / Recommended 8GB
Comfortable
Llama 3.1 8B (Q5)
Large language models (LLM)
Balanced quantization
Minimum 7GB / Recommended 9GB
Comfortable
Llama 3.1 8B (Q8)
Large language models (LLM)
Near full quality
Minimum 10GB / Recommended 12GB
Comfortable
Qwen 2.5 7B (Q4)
Large language models (LLM)
Strong in Japanese, by Alibaba
Minimum 5GB / Recommended 7GB
Comfortable
Gemma 2 9B (Q4)
Large language models (LLM)
Mid-size model by Google
Minimum 6GB / Recommended 8GB
Comfortable
Phi-4 14B (Q4)
Large language models (LLM)
Compact, high-performance model by Microsoft
Minimum 9GB / Recommended 12GB
Comfortable
Qwen 2.5 14B (Q4)
Large language models (LLM)
Mid-size model by Alibaba
Minimum 9GB / Recommended 12GB
Comfortable
DeepSeek-R1 Distill 7B (Q4)
Large language models (LLM)
Specialized for reasoning, lightweight
Minimum 5GB / Recommended 7GB
Comfortable
ELYZA-Llama 8B (Q4)
Large language models (LLM)
Llama specialized for Japanese
Minimum 6GB / Recommended 8GB
Comfortable
LLaVA 1.6 7B (Q4)
Large language models (LLM)
Multimodal model for image understanding
Minimum 7GB / Recommended 9GB
Comfortable
Qwen2-VL 7B (Q4)
Large language models (LLM)
Video and image understanding
Minimum 7GB / Recommended 9GB
Comfortable
Qwen3 8B (Q4)
Large language models (LLM)
2025 generation, efficient 8B with switchable thinking mode
Minimum 5GB / Recommended 6GB
Comfortable
Qwen3 14B (Q4)
Large language models (LLM)
2025 generation, balanced 14B
Minimum 8GB / Recommended 10GB
Comfortable
Qwen3.5 9B (Q4)
Large language models (LLM)
February 2026 version, 262K long context
Minimum 6GB / Recommended 8GB
Comfortable
Gemma 3 12B (Q4)
Large language models (LLM)
Google Gemma 3, mid-size, accepts image input
Minimum 7GB / Recommended 9GB
Comfortable
Gemma 4 E2B (Q4)
Large language models (LLM)
Google, April 2026, smallest phone-class model, accepts image and audio input
Minimum 4GB / Recommended 6GB
Comfortable
Qwen3.5 2B (Q4)
Large language models (LLM)
Alibaba, 2026, small multimodal model with thinking mode
Minimum 4GB / Recommended 6GB
Comfortable
Gemma 4 E4B (Q4)
Large language models (LLM)
Google, April 2026, lightweight multimodal, Apache 2.0
Minimum 6GB / Recommended 8GB
Comfortable
Qwen3.5 4B (Q4)
Large language models (LLM)
Alibaba, 2026, high performance for 4B class, 262K context
Minimum 6GB / Recommended 8GB
Comfortable
Gemma 4 12B (Q4)
Large language models (LLM)
Google, added June 2026, mid-size model for image and audio
Minimum 8GB / Recommended 10GB
Comfortable
Ministral 3 14B (Q4)
Large language models (LLM)
Mistral, December 2025, 14B, a reasoning version is also available
Minimum 10GB / Recommended 12GB
Comfortable
llm-jp-4.1 8B thinking (Q4)
Large language models (LLM)
LLM-jp, Sep 2026, Japanese reasoning model, 8B, Apache 2.0
Minimum 7GB / Recommended 10GB
Comfortable
llm-jp-4 VL 9B (Q4)
Large language models (LLM)
LLM-jp, Aug 2026, Japanese 9B that can read images, Apache 2.0
Minimum 7GB / Recommended 10GB
Comfortable
MiniCPM5 2B (Q4)
Large language models (LLM)
OpenBMB, Sep 2026, small 2.5B model with long context and tool calling, Apache 2.0
Minimum 4GB / Recommended 6GB
Comfortable
Gemma 4 E4B (Q8)
Large language models (LLM)
Near full quality
Minimum 10GB / Recommended 12GB
Comfortable
Qwen3 8B (Q8)
Large language models (LLM)
Near full quality
Minimum 11GB / Recommended 12GB
△ Barely
Ministral 3 8B (FP8)
Large language models (LLM)
Mistral, December 2025, supports Japanese and image input, official FP8 needs 12GB
Minimum 12GB / Recommended 16GB
△ Barely
Qwen3.5 9B (Q8)
Large language models (LLM)
Near full quality
Minimum 12GB / Recommended 16GB

Speech and music

Comfortable
Whisper Tiny
Speech and music
Ultra-lightweight speech recognition
Minimum 1GB / Recommended 2GB
Comfortable
Whisper Small
Speech and music
Lightweight speech recognition
Minimum 2GB / Recommended 3GB
Comfortable
Whisper Medium
Speech and music
Standard speech recognition
Minimum 5GB / Recommended 6GB
Comfortable
Whisper Large v3
Speech and music
High-accuracy speech recognition
Minimum 10GB / Recommended 12GB
Comfortable
Whisper Turbo
Speech and music
Large-level accuracy, fast
Minimum 6GB / Recommended 8GB
Comfortable
XTTS v2 (voice cloning)
Speech and music
Voice-cloning TTS
Minimum 4GB / Recommended 6GB
Comfortable
RVC (real-time voice conversion)
Speech and music
Voice conversion for streaming
Minimum 4GB / Recommended 8GB
Comfortable
Bark TTS
Speech and music
Multilingual TTS with emotional expression, 8GB for the small model
Minimum 8GB / Recommended 12GB
Comfortable
MusicGen Medium
Speech and music
Meta, music generation
Minimum 6GB / Recommended 8GB
Comfortable
AudioCraft / AudioGen
Speech and music
Sound effect generation
Minimum 6GB / Recommended 10GB
Comfortable
Stable Audio Open
Speech and music
By Stability AI, music
Minimum 8GB / Recommended 12GB
Comfortable
Whisper Base
Speech and music
OpenAI, 74M, lightweight speech recognition
Minimum 1GB / Recommended 2GB
Comfortable
Kokoro-82M
Speech and music
82M ultra-lightweight TTS, multilingual including Japanese, practical on CPU
Minimum 1GB / Recommended 2GB
Comfortable
Parakeet TDT 0.6B v3
Speech and music
NVIDIA, 25 European languages, no Japanese support, very fast
Minimum 2GB / Recommended 4GB
Comfortable
Parakeet TDT-CTC 0.6B ja
Speech and music
NVIDIA, Japanese only, with punctuation, runs on NeMo
Minimum 2GB / Recommended 4GB
Comfortable
Style-Bert-VITS2 (JP-Extra)
Speech and music
A standard Japanese TTS, with emotion style control. Inference works on CPU, training needs 8GB or more
Minimum 2GB / Recommended 4GB
Comfortable
faster-whisper large-v3 (INT8)
Speech and music
Whisper on CTranslate2, faster and lighter on memory than the original
Minimum 3GB / Recommended 4GB
Comfortable
kotoba-whisper v2.2
Speech and music
Kotoba Technologies, specialized for Japanese, about 6x faster than large-v3, with speaker separation and punctuation
Minimum 4GB / Recommended 6GB
Comfortable
Qwen3-ASR 0.6B
Speech and music
Alibaba, lightweight, for high-volume processing
Minimum 4GB / Recommended 6GB
Comfortable
GPT-SoVITS v2Pro
Speech and music
Clones a voice from 1 minute of audio, supports Japanese
Minimum 4GB / Recommended 6GB
Comfortable
Qwen3-TTS 0.6B
Speech and music
Alibaba, lightweight TTS, supports streaming
Minimum 4GB / Recommended 6GB
Comfortable
Irodori-TTS v4.1 Small
Speech and music
Japanese-only TTS, voice cloning, speaking style set with emoji, MIT
Minimum 4GB / Recommended 6GB
Comfortable
faster-whisper large-v3 (FP16)
Speech and music
Whisper on CTranslate2, same accuracy at higher speed
Minimum 5GB / Recommended 6GB
Comfortable
Qwen3-ASR 1.7B
Speech and music
Alibaba, January 2026, 30 languages including Japanese, among the best open speech recognition
Minimum 6GB / Recommended 8GB
Comfortable
F5-TTS v1
Speech and music
Zero-shot voice cloning TTS from reference audio
Minimum 6GB / Recommended 8GB
Comfortable
Qwen3-TTS 1.7B
Speech and music
Alibaba, January 2026, 10 languages including Japanese, voice design and cloning
Minimum 6GB / Recommended 8GB
Comfortable
Chatterbox Multilingual
Speech and music
Resemble AI, 23 languages including Japanese, voice cloning, MIT
Minimum 6GB / Recommended 8GB
Comfortable
ACE-Step 1.5
Speech and music
April 2026, generates songs with vocals, 2B model, MIT
Minimum 6GB / Recommended 12GB
Comfortable
VibeVoice-ASR-Streaming 1.5B
Speech and music
Microsoft, Sep 2026, streaming speech recognition, MIT
Minimum 8GB / Recommended 10GB
Comfortable
Granite Speech 5.0 470M
Speech and music
IBM, Aug 2026, lightweight 470M speech recognition, Apache 2.0
Minimum 3GB / Recommended 4GB
△ Barely
MusicGen Large
Speech and music
High-quality music generation
Minimum 10GB / Recommended 14GB
△ Barely
ACE-Step 1.5 XL
Speech and music
Higher-quality version. Under 20GB needs CPU offloading and quantization
Minimum 12GB / Recommended 24GB
△ Barely
YuE2-3B
Speech and music
m-a-p, Sep 2026, generates songs with vocals, about 11GB peak on an RTX 4090, non-commercial license
Minimum 12GB / Recommended 16GB
△ Barely
VibeVoice-ASR-Streaming 7B (Q8)
Speech and music
GGUF Q8, runs with audio-cpp
Minimum 12GB / Recommended 16GB

AI training and fine-tuning

Comfortable
LoRA training (SD1.5)
AI training and fine-tuning
Training characters and styles
Minimum 6GB / Recommended 8GB
△ Barely
LoRA training (SDXL)
AI training and fine-tuning
LoRA for SDXL
Minimum 12GB / Recommended 16GB
△ Barely
Llama LoRA (7B)
AI training and fine-tuning
Lightweight LLM fine-tuning
Minimum 12GB / Recommended 16GB
Models That Cannot Run (95)

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Other GPUs in the Same Series

NVIDIA H100 SXM NVIDIA H100 PCIe NVIDIA A100 SXM NVIDIA A100 PCIe NVIDIA V100 SXM2 NVIDIA RTX 6000 Ada NVIDIA RTX A6000 NVIDIA RTX A5000 NVIDIA Quadro RTX 8000 NVIDIA Quadro RTX 6000 NVIDIA RTX A4000 NVIDIA Quadro P6000

→ All GPUs / → Bottleneck Checker (Both Directions)

GPUs Commonly Compared with RTX 4070 Ti

RTX 4070 Ti vs RTX 5070 RTX 4070 Ti vs RTX 4070 SUPER RTX 4070 Ti vs RTX 4090 Laptop GPU RTX 4070 Ti vs RTX 3090 Ti RTX 4070 Ti vs RTX 3090 RTX 4070 Ti vs RTX 3080 Ti

→ Compare Other Models / → Check Whether an Upgrade Is Worthwhile

Frequently Asked Questions About CPU Bottlenecks and Compatibility for RTX 4070 Ti

Which CPU minimizes the CPU bottleneck for RTX 4070 Ti(RTX4070Ti / 4070Ti)?

In our estimate, the best-balanced options are Core i7-13700K for Intel (estimated bottleneck: about 0%) and Ryzen 9 7950X3D for AMD (about 0%). A CPU-to-GPU performance ratio near 0.9:1 tends to use both parts effectively. See the top 10 compatible CPUs in the table on this page.

Which CPUs pair poorly with RTX 4070 Ti and should be avoided?

As a guide, CPUs such as Core i5-12400、Ryzen 9 3950X、Ryzen 9 3900XT、Ryzen 7 3800XT push the bottleneck above 25% and waste much of the GeForce RTX 4070 Ti performance.

How much VRAM does GeForce RTX 4070 Ti have, and which generative AI models can it run?

GeForce RTX 4070 Ti has 12GB of VRAM. It can comfortably run about 87 models, including Stable Diffusion and LLMs (for example, SD 1.5 (Q4 quantized), Stable Diffusion 1.5, SDXL Turbo).

What is the power draw (TDP) of GeForce RTX 4070 Ti?

GeForce RTX 4070 Ti has a power draw (TDP) of 285W. Choose a power supply that covers the GPU TDP plus CPU and other component power draw, with additional headroom. Check the actual CPU pairing balance in the bottleneck diagnosis above.

Can GeForce RTX 4070 Ti be used for both gaming and generative AI?

Its performance score is 28,000 points. CPU balance matters for gaming, while VRAM (12GB) matters for generative AI. Use the top 10 CPU list and AI model list above to check your use case.