AMD · RDNA 4 · 2025
AMD Radeon RX 9070 XT for local AI
A solid 16GB RDNA 4 card with improving ROCm support, trailing the RTX 5070 Ti on bandwidth.
Updated · Speeds marked ~ are estimates; seemethodology
- VRAM
- 16GB
- Bandwidth
- 640 GB/s
- Power
- 304W
- Runs well
- 6 models
RX 9070 XT
Typically about $800
Can the RX 9070 XT run LLMs?
The RX 9070 XT has 16GB of GDDR6 and 640 GB/s of memory bandwidth, which decides how big a model fits and how fast it generates text. It comfortably runs models up to about 15B parameters: the largest in our catalog is Phi-4 at Q5_K_M (13GB with 8K context, ~37 tokens/sec). Our top all-round pick for it is Qwen3.8 27B (Q3_K_M, ~30 tokens/sec). Llama 3.3 70B Instruct only runs with partial CPU offload, at about 1.4 tokens/sec with CPU offload.
Recommendations
Best models for the RX 9070 XT
Best overall · also coding, reasoning, vision, largest that fits
Qwen3.8 27BQ3_K_M · 15GB · ~30 tokens/sec
Fits, tightRunner-up
Qwen3.5 9BQ8_0 · 12GB · ~36 tokens/sec
Runs wellFastest good model
Gemma 4 26B A4BQ3_K_M · 14GB · ~90 tokens/sec
Fits, tight
Compatibility
What runs on the RX 9070 XT
Every current model in our catalog, at the best quantization that fits in 16GB with 8K tokens of context. "Partial offload" means part of the model runs from system RAM (we assume 64GB), which is much slower.
| Model | Parameters | Best quant | Memory | Speed | Verdict |
|---|---|---|---|---|---|
| Gemma 4 E4B | 8B | Q8_0 | 10 GB | ~41 tok/s | Runs well |
| Qwen3.5 9B | 9B | Q8_0 | 12 GB | ~36 tok/s | Runs well |
| Phi-4 | 14.7B | Q5_K_M | 13 GB | ~37 tok/s | Runs well |
| gpt-oss-20b | 20.9B (3.6B active) | MXFP4 | 15 GB | ~75 tok/s | Fits, tight |
| Gemma 4 26B A4B | 26B (3.8B active) | Q3_K_M | 14 GB | ~90 tok/s | Fits, tight |
| Qwen3.8 27B | 27B | Q3_K_M | 15 GB | ~30 tok/s | Fits, tight |
| Gemma 4 31B | 31B | Q4_K_M | 22 GB | ~5.4 tok/s | Partial offload |
| Qwen3.6 35B-A3B | 35B (3B active) | Q4_K_M | 24 GB | ~41 tok/s | Partial offload |
| GLM-4.5-Air | 106B (12B active) | — | — | — | Won't fitWhat it needs |
| Llama 4 Scout | 109B (17B active) | — | — | — | Won't fitWhat it needs |
| gpt-oss-120b | 117B (5.1B active) | — | — | — | Won't fitWhat it needs |
| Qwen3.5 122B-A10B | 122B (10B active) | — | — | — | Won't fitWhat it needs |
| DeepSeek V4 Flash | 284B (13B active) | — | — | — | Won't fitWhat it needs |
| GLM-5.3-Flash | 320B (18B active) | — | — | — | Won't fitWhat it needs |
| GLM-5.3 | 744B (40B active) | — | — | — | Won't fitWhat it needs |
Performance
RX 9070 XT vs. alternatives on Qwen3.8 27B
Generation speed in tokens per second for a single user. Token generation is limited mostly by memory bandwidth, which is why bandwidth predicts these results so well.
RTX 5070 Ti
Q3_K_M · 16GB
~51tok/s
RX 7900 XTX
Q4_K_M · 24GB
~36tok/s
RX 9070 XT
Q3_K_M · 16GB
~30tok/s
R9700
Q6_K · 32GB
~18tok/s
Measured
RX 9070 XT benchmark results
| Model | Quant | Runtime | Generation | Prompt | Source |
|---|---|---|---|---|---|
| Llama 2 7B Chat | Q4_0 | llama.cpp (Vulkan) | 135 tok/s | 5035 tok/s | llama.cpp discussion #10879: Performance of llama.cpp with Vulkan · October 2026 |
| Llama 2 7B Chat | Q4_0 | llama.cpp (ROCm (HIP)) | 100 tok/s | 5055 tok/s | llama.cpp discussion #15021: Performance of llama.cpp on AMD ROCm (HIP) · October 2026 |
Our take
Should you buy the RX 9070 XT for AI?
The Radeon RX 9070 XT uses the Navi 48 chip with 16GB of GDDR6 on a 256-bit bus for 640 GB/s. RDNA 4 adds much faster AI matrix hardware than RDNA 3, ROCm now supports the card on Linux, and Vulkan works everywhere. It runs 14B models at 8 bit and 24B models at 4 bit, but 16GB limits anything larger. Prices rose to about $800 new in October 2026 after AMD raised RX 9000 pricing, which narrows its value advantage, though it still costs about $400 less than an RTX 5070 Ti.
What we like
- Cheaper than NVIDIA's comparable 16GB cards
- Much faster AI hardware than RDNA 3
- Good Vulkan and ROCm support in llama.cpp
Watch out for
- 640 GB/s trails the RTX 5070 Ti's 896 GB/s
- Some tools remain CUDA-only
- 16GB limits model size
Best for: AMD gaming PCs that also run local models · Linux users who prefer open drivers
Specifications
RX 9070 XT specs that matter for AI
- Memory
- 16GB GDDR6
- Memory bandwidth
- 640 GB/s
- Memory bus
- 256-bit
- Architecture
- RDNA 4
- Power
- 304W
- Interface
- PCIe 5.0 x16
- Released
- 2025
- Launch price
- $599
- Street price (new)
- ~$800 (2026-10)
- Street price (used)
- ~$720 (2026-10)
- Software
- ROCm, Vulkan
Sources: Wikipedia, Radeon RX 9000 series
Cross-shop
Alternatives to the RX 9070 XT
Frequently asked questions
How much VRAM does the RX 9070 XT have?
The AMD Radeon RX 9070 XT has 16GB of GDDR6 with 640 GB/s of memory bandwidth on a 256-bit bus.
What is the largest LLM the RX 9070 XT can run?
Fully in GPU memory, the largest model in our catalog that runs comfortably is Phi-4 (14.7B) at Q5_K_M, using about 13GB with 8K context at ~37 tokens/sec.
Can the RX 9070 XT run Llama 3.3 70B?
Only with partial CPU offload. At Q4_K_M the model needs about 47GB with 8K context, so part of it spills into system RAM and speed drops to about 1.4 tokens/sec with CPU offload. For usable 70B speeds you want 48GB of VRAM or more (for example two 24GB cards).
What is the best LLM to run on the RX 9070 XT?
Our top pick is Qwen3.8 27B at Q3_K_M, which fits in 16GB with room for 8K of context and runs at ~30 tokens/sec. See our full list of the best models for the RX 9070 XT for coding, reasoning, and vision picks.
Is the RX 9070 XT good for local AI in 2026?
A solid 16GB RDNA 4 card with improving ROCm support, trailing the RTX 5070 Ti on bandwidth.