การ์ดจอ NVIDIA ทุกรุ่น
การ์ดจอ NVIDIA ทุกรุ่น GeForce RTX 4000 Ada Lovelace DLSS 3 Ray Tracing CUDA AI ML เกม 1080p 1440p 4K
| รุ่น | CUDA Cores | VRAM | TDP | ราคา (บาท) | เหมาะกับ |
|---|---|---|---|---|---|
| RTX 4060 | 3072 | 8GB | 115W | 10-13K | เกม 1080p |
| RTX 4060 Ti | 4352 | 8/16GB | 160W | 13-18K | เกม 1080p Ultra |
| RTX 4070 | 5888 | 12GB | 200W | 18-22K | เกม 1440p |
| RTX 4070 Super | 7168 | 12GB | 220W | 20-25K | เกม 1440p แนะนำ |
| RTX 4070 Ti Super | 8448 | 16GB | 285W | 26-32K | เกม 1440p Ultra |
| RTX 4080 Super | 10240 | 16GB | 320W | 35-42K | เกม 4K |
| RTX 4090 | 16384 | 24GB | 450W | 55-70K | 4K Ultra / AI |
Specifications
# === NVIDIA RTX 4000 Series Specs ===
from dataclasses import dataclass
@dataclass
class GPUSpec:
model: str
cuda_cores: int
vram: str
memory_bus: str
boost_clock: int
tdp: int
psu_rec: str
price_thb: str
perf_1440p: str
specs = [
GPUSpec("RTX 4060", 3072, "8GB GDDR6", "128-bit",
2460, 115, "PSU 500W+ (8-pin x1)",
"10,000-13,000", "55 FPS (1440p Ultra Avg)"),
GPUSpec("RTX 4060 Ti 8GB", 4352, "8GB GDDR6", "128-bit",
2535, 160, "PSU 550W+ (8-pin x1)",
"13,000-16,000", "65 FPS"),
GPUSpec("RTX 4070", 5888, "12GB GDDR6X", "192-bit",
2475, 200, "PSU 650W+ (12VHPWR)",
"18,000-22,000", "80 FPS"),
GPUSpec("RTX 4070 Super", 7168, "12GB GDDR6X", "192-bit",
2475, 220, "PSU 650W+ (12VHPWR)",
"20,000-25,000", "90 FPS"),
GPUSpec("RTX 4070 Ti Super", 8448, "16GB GDDR6X", "256-bit",
2610, 285, "PSU 700W+ (12VHPWR)",
"26,000-32,000", "100 FPS"),
GPUSpec("RTX 4080 Super", 10240, "16GB GDDR6X", "256-bit",
2550, 320, "PSU 750W+ (12VHPWR)",
"35,000-42,000", "120 FPS"),
GPUSpec("RTX 4090", 16384, "24GB GDDR6X", "384-bit",
2520, 450, "PSU 850W+ (12VHPWR)",
"55,000-70,000", "160+ FPS (4K Ultra)"),
]
print("=== NVIDIA RTX 4000 Specs ===")
for s in specs:
print(f"\n [{s.model}]")
print(f" CUDA: {s.cuda_cores} | VRAM: {s.vram} ({s.memory_bus})")
print(f" Boost: {s.boost_clock} MHz | TDP: {s.tdp}W")
print(f" PSU: {s.psu_rec}")
print(f" Price: {s.price_thb} บาท | Perf: {s.perf_1440p}")
AI/ML Usage
# === NVIDIA GPU for AI/ML ===
@dataclass
class AIUseCase:
use_case: str
min_vram: str
recommended_gpu: str
framework: str
note: str
ai_cases = [
AIUseCase("LLM Inference 7B (Q4)",
"6GB+ VRAM",
"RTX 4060 8GB (พอดี) RTX 4070 12GB (สบาย)",
"llama.cpp / Ollama / text-gen-webui",
"Q4 Quantized 7B Model ≈ 4-5GB VRAM"),
AIUseCase("LLM Inference 13B (Q4)",
"10GB+ VRAM",
"RTX 4070 Ti Super 16GB (แนะนำ)",
"llama.cpp / Ollama / vLLM",
"Q4 Quantized 13B Model ≈ 8-10GB VRAM"),
AIUseCase("LLM Inference 70B (Q4)",
"20GB+ VRAM",
"RTX 4090 24GB (พอดี) Multi-GPU",
"llama.cpp / vLLM / TGI",
"Q4 Quantized 70B Model ≈ 20-24GB VRAM"),
AIUseCase("Stable Diffusion (SDXL)",
"8GB+ VRAM",
"RTX 4060 8GB (พอ) RTX 4070+ (เร็ว)",
"Automatic1111 / ComfyUI / Forge",
"SDXL ≈ 6-8GB VRAM Generation 10-30 วินาที"),
AIUseCase("Fine-tuning (LoRA)",
"12GB+ VRAM",
"RTX 4070 Super 12GB+ RTX 4090 24GB",
"Unsloth / Axolotl / PEFT",
"LoRA Fine-tune 7B ≈ 10-12GB VRAM"),
AIUseCase("Training (Full)",
"24GB+ VRAM",
"RTX 4090 24GB (หรือ Multi-GPU / Cloud)",
"PyTorch / TensorFlow / DeepSpeed",
"Full Training ต้อง VRAM มาก ใช้ Cloud ดีกว่า"),
]
print("=== AI/ML GPU Guide ===")
for a in ai_cases:
print(f"\n [{a.use_case}] Min VRAM: {a.min_vram}")
print(f" GPU: {a.recommended_gpu}")
print(f" Framework: {a.framework}")
print(f" Note: {a.note}")
Buying Guide
# === GPU Buying Guide ===
@dataclass
class BuyingGuide:
budget: str
recommended: str
use_case: str
psu: str
guides = [
BuyingGuide("10,000-13,000 บาท",
"RTX 4060",
"เกม 1080p High-Ultra | AI Inference เล็ก | Streaming",
"PSU 500W+ (8-pin x1)"),
BuyingGuide("13,000-20,000 บาท",
"RTX 4060 Ti 16GB หรือ RTX 4070",
"เกม 1080p Ultra / 1440p Medium | Stable Diffusion",
"PSU 550-650W+ (8-pin x1 / 12VHPWR)"),
BuyingGuide("20,000-26,000 บาท",
"RTX 4070 Super ★ แนะนำ",
"เกม 1440p High-Ultra | AI Inference | Content Creation",
"PSU 650W+ (12VHPWR)"),
BuyingGuide("26,000-35,000 บาท",
"RTX 4070 Ti Super",
"เกม 1440p Ultra | Ray Tracing | AI 13B Models",
"PSU 700W+ (12VHPWR)"),
BuyingGuide("35,000-45,000 บาท",
"RTX 4080 Super",
"เกม 4K High | Ray Tracing 1440p | Content Creation Pro",
"PSU 750W+ (12VHPWR)"),
BuyingGuide("55,000+ บาท",
"RTX 4090",
"เกม 4K Ultra | AI Training | LLM 70B | Professional",
"PSU 850W+ (12VHPWR)"),
]
print("=== Buying Guide ===")
for g in guides:
print(f"\n Budget: {g.budget}")
print(f" ★ {g.recommended}")
print(f" Use: {g.use_case}")
print(f" PSU: {g.psu}")
เคล็ดลับ
- RTX 4070 Super: คุ้มค่าสุดสำหรับ 1440p Gaming + AI Inference
- DLSS 3: เปิด DLSS 3 เพิ่ม FPS 50-100% แทบไม่เสีย Quality
- VRAM: เลือก 12GB+ สำหรับเกม 2024+ ที่ใช้ VRAM มากขึ้น
- AI: สำหรับ AI ดู VRAM เป็นหลัก RTX 4060 8GB ก็ใช้ได้สำหรับ 7B Model
- PSU: ตรวจ PSU Wattage + 12VHPWR Connector ก่อนซื้อ
NVIDIA GeForce RTX 4000 Series มีรุ่นอะไรบ้าง
RTX 4060 4060Ti 4070 4070Super 4070TiSuper 4080Super 4090 Ada Lovelace DLSS 3 Ray Tracing CUDA Tensor AV1 Reflex
เปรียบเทียบแต่ละรุ่นอย่างไร
RTX 4070 Super คุ้มค่าสุด RTX 4060 ถูกสุด RTX 4090 แรงสุด VRAM 8-24GB TDP 115-450W FPS 55-160+ Ray Tracing
ใช้สำหรับ AI/ML ได้ไหม
CUDA Tensor Cores PyTorch TensorFlow LLM 7B RTX 4060 13B RTX 4070TiSuper 70B RTX 4090 Stable Diffusion LoRA Training VRAM
วิธีเลือกทำอย่างไร
งบ 10K RTX 4060 งบ 20-25K RTX 4070 Super งบ 55K+ RTX 4090 เกม 1080p 1440p 4K AI PSU Case Connector VRAM
สรุป
การ์ดจอ NVIDIA ทุกรุ่น RTX 4060-4090 Ada Lovelace DLSS 3 Ray Tracing CUDA AI ML VRAM RTX 4070 Super คุ้มค่าสุด
