RX 9070 XT ¥3990 Deal Check

RX 9070 XT ¥3990 Deal Check | Generated by AI

Home 2026.07

Question: Is this used 瀚铠 RX 9070 XT 16GB 黑色超合金 OC for ¥3990 CNY a good deal?

Answer:

AMD Radeon RX 9070 XT is a very interesting card for your use case (AI experiments + gaming), but this specific second-hand deal needs some checking.

Price evaluation

¥3990 CNY for a near-new RX 9070 XT 16GB is reasonable, but not an amazing bargain.

Typical positioning:

GPU	VRAM	AI / ROCm	Approx value
RTX 4070	12GB	Excellent CUDA	~¥3000 used
RTX 3090	24GB	Good CUDA	~¥4500-6000 used
RX 9070 XT	16GB	Improving ROCm	~¥4000 new/used
RTX 5070 Ti	16GB	Excellent CUDA	higher

The RX 9070 XT is basically a gaming monster, but for AI it has a key limitation:

CUDA ecosystem: NVIDIA wins massively.
ROCm: usable, improving, but still not as smooth.

For your situation (you already:

trained GPT-2 124M on RTX 4070
bought MI50 16GB HBM2 for ROCm experiments
care about LLM training/inference)

the question is not FPS. It is software ecosystem.

RX 9070 XT strengths

1. 16GB VRAM

This is a big upgrade over RTX 4070 12GB.

For LLM:

7B model FP16:
7B × 2 bytes ≈ 14GB

So:

RTX 4070 12GB → cannot comfortably run many 7B FP16 models
RX 9070 XT 16GB → possible

For quantized:

7B Q4:
~4-5GB

easy.

2. RDNA4 compute improvement

RX 9070 XT:

4096 stream processors
16GB GDDR6
~640GB/s bandwidth
BF16/FP16 acceleration

Much stronger than your RTX 4070.

But for AI development

Example:

PyTorch CUDA

model.to("cuda")

works.

ROCm

pip install torch --index-url https://download.pytorch.org/whl/rocm6.3

then:

model.to("cuda")

also works.

But the pain points:

some libraries only test CUDA
FlashAttention support
vLLM compatibility
xformers
Triton kernels

NVIDIA is still ahead.

Compared with your current setup

Your current:

RTX 4070 12GB
+
MI50 16GB HBM2

Actually gives you something unique:

RTX 4070 → CUDA ecosystem
MI50 → ROCm/HBM experiments

Buying RX9070XT means:

RTX4070 -> gaming/AI CUDA
RX9070XT -> ROCm consumer card
MI50 -> ROCm professional card

Three GPU worlds.

Fun for learning, but not necessarily efficient.

Check before buying

I would ask seller:

1. Exact BIOS

Run:

GPU-Z

Check:

BIOS version
memory type
PCIe link
power limit

2. Stress test

Run:

3DMark Time Spy

or:

FurMark 20 minutes

Watch:

hotspot temperature
clock stability
fan noise

3. Verify warranty

“个人送保 28年5月” is valuable.

Confirm:

serial number photo
invoice
JD order screenshot

My judgment for you

Given your profile:

If your goal is

AI training / LLM engineering

I would prefer:

Used RTX 3090 24GB

because:

24GB VRAM > 16GB VRAM
CUDA > ROCm

especially for:

LoRA
QLoRA
LLM fine-tuning
vLLM

If your goal is

learn ROCm + gaming + future AMD AI stack

RX9070 XT ¥3990 is a good buy.

My ranking for your AI experiments:

RTX3090 24GB used (~4500-5500)
        >
RX9070XT 16GB (~3990)
        >
RTX4070 12GB
        >
MI50 16GB (interesting but old)

For you personally, I would probably not replace RTX4070 with RX9070XT. I would keep RTX4070 + MI50, save money, and wait for a cheap 24GB NVIDIA card. The jump from 12GB → 16GB is nice; the jump from 12GB → 24GB changes what models you can train.

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