RTX 5070 Ti 16GB vs Radeon RX 9070 XT 16GB for Local LLMs
Both have 16.0 GB, so they run the same models. The RTX 5070 Ti 16GB generates tokens about 63% faster. Below: speeds on seven popular models, the models only one card can run, and our verdict.
Specs that matter for AI
| RTX 5070 Ti 16GB | Radeon RX 9070 XT 16GB | |
|---|---|---|
| Memory | 16 GB | 16 GB |
| GPU-usable memory | 16.0 GB | 16.0 GB |
| Bandwidth | 896 GB/s | 640 GB/s |
| Architecture | Blackwell | RDNA 4 |
| Released | 2025-02 | 2025-03 |
| Llama 3.1 8B Q4_K_M | ~104 tok/s | ~64 tok/s |
Speed and fit by model
Q4_K_M (or native format) with 8K context.
| Model | VRAM | RTX 5070 Ti 16GB | Radeon RX 9070 XT 16GB |
|---|---|---|---|
| Llama 3.1 8B | 6.3 GB | Fits ~104 tok/s | Fits ~64 tok/s |
| Qwen 3 14B | 10.5 GB | Fits ~59 tok/s | Fits ~36 tok/s |
| gpt-oss-20b | 13.9 GB | Fits ~151 tok/s | Fits ~106 tok/s |
| Qwen 3 30B-A3B | 18.8 GB | 80% on GPU ~51 tok/s | 80% on GPU ~46 tok/s |
| Qwen 3 32B | 21.4 GB | 70% on GPU ~5.7 tok/s | 70% on GPU ~5.2 tok/s |
| Llama 3.3 70B | 43.2 GB | 35% on GPU ~1.4 tok/s | 35% on GPU ~1.4 tok/s |
| gpt-oss-120b | 62.0 GB | Too small | Too small |
Verdict
Both are 16 GB cards, so model capacity is identical. The 5070 Ti has more bandwidth (896 vs 640 GB/s) and the CUDA ecosystem, so it generates tokens faster and supports more tools. The 9070 XT is usually cheaper and works well with llama.cpp-based apps.
Which should you buy?
Choose the RTX 5070 Ti 16GB if…
- You want the fastest 16 GB card in this price range.
- You use CUDA-first tools such as vLLM or ComfyUI.
- You want FP4 support.
Choose the Radeon RX 9070 XT 16GB if…
- You want 16 GB for less money.
- You use llama.cpp-based apps.
- You also game and prefer AMD.
Best quality and longest context on each card
The highest-quality quantization that fits fully at 8K context, and the longest context that fits at Q4_K_M with an FP16 cache.
| Model | RTX 5070 Ti 16GB: best quant | Radeon RX 9070 XT 16GB: best quant | RTX 5070 Ti 16GB: max context | Radeon RX 9070 XT 16GB: max context |
|---|---|---|---|---|
| Qwen 3.5 9B | Q8_0 | Q8_0 | 256K | 256K |
| Qwen 3 14B | Q6_K | Q6_K | 37K | 37K |
| gpt-oss-20b | MXFP4 (official) | MXFP4 (official) | 55K | 55K |
| Qwen 3.6 27B | IQ4_XS | IQ4_XS | – | – |
| Qwen 3 32B | Q2_K | Q2_K | – | – |
| Llama 3.3 70B | Does not fit | Does not fit | – | – |
Image generation
Best weight precision for image models with model swapping, at each model's default resolution. Image generation is also limited by compute, so the card with more tensor-core throughput finishes each image faster even when both fit.
| Model | RTX 5070 Ti 16GB | Radeon RX 9070 XT 16GB |
|---|---|---|
| SDXL 1.0 | FP16 / BF16 | FP16 / BF16 |
| FLUX.1 [dev] | FP8 | FP8 |
| Qwen-Image | GGUF Q5_K_S | GGUF Q5_K_S |
| Wan 2.2 A14B (T2V / I2V) | GGUF Q5_K_S | GGUF Q5_K_S |
Frequently asked questions
Is the RTX 5070 Ti 16GB or Radeon RX 9070 XT 16GB better for local LLMs?
Both are 16 GB cards, so model capacity is identical. The 5070 Ti has more bandwidth (896 vs 640 GB/s) and the CUDA ecosystem, so it generates tokens faster and supports more tools. The 9070 XT is usually cheaper and works well with llama.cpp-based apps.
Which is faster for LLM inference?
The RTX 5070 Ti 16GB, by about 63% for token generation on models that fit both (about 104 vs 64 tokens/s on Llama 3.1 8B Q4_K_M).
Which can run bigger models?
Neither: both have 16.0 GB usable, so they run the same models.