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การ์ดจอ NVIDIA ทุกรุ่น GeForce RTX 4000 Ada Lovelace DLSS 3 Ray Tracing CUDA AI ML เกม 1080p 1440p 4K

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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

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