Best AI Models for AMD Radeon RX 6700 XT (12.0GB)
12 GB is the sweet spot for entry into local AI. It runs 7B–13B models at good quality quantizations, making it a practical and affordable starting point for running LLMs on your own hardware.
This memory tier, common on GPUs like the RTX 3060 12GB, is surprisingly capable for local AI. You can run Llama 3 8B, Mistral 7B, and similar 7B models at Q4_K_M quantization with decent token generation speed. Smaller models like Phi 3 Mini (3.8B) run at Q6 or Q8 with room to spare. Reaching up to 13B models is possible at Q2–Q3 quantization, though quality trade-offs become more noticeable.
Runs Well
- 7B models at Q4_K_M quality
- Small models (3B–4B) at Q5–Q8
- Chat and coding assistants for everyday use
Challenging
- 13B models only at Q2–Q3 (lower quality)
- 14B+ models do not fit
- Context windows limited for 7B+ models
What LLMs Can AMD Radeon RX 6700 XT Run?
80 models · 9 excellent · 10 good
Showing compatibility for AMD Radeon RX 6700 XT
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
Q4_K_M·39.8 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.3 GB | 39.8 t/s | 131K | FAIR FIT | B59 |
Q4_K_M·42.3 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 5.0 GB | 42.3 t/s | 33K | FAIR FIT | B57 |
Q4_K_M·34.6 t/s tok/s·8K ctx·GOOD FIT | Q4_K_M | 6.1 GB | 34.6 t/s | 8K | GOOD FIT | A66 |
Q4_K_M·39.7 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.3 GB | 39.7 t/s | 131K | FAIR FIT | B59 |
Q4_K_M·35.1 t/s tok/s·33K ctx·GOOD FIT | Q4_K_M | 6.0 GB | 35.1 t/s | 33K | GOOD FIT | A65 |
Q4_K_M·42.9 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 4.9 GB | 42.9 t/s | 33K | FAIR FIT | B56 |
Q4_K_M·38.3 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.5 GB | 38.3 t/s | 131K | FAIR FIT | B61 |
Q4_K_M·36.7 t/s tok/s·66K ctx·FAIR FIT | Q4_K_M | 5.8 GB | 36.7 t/s | 66K | FAIR FIT | B63 |
IQ2_XXS·20.6 t/s tok/s·262K ctx·GOOD FIT | IQ2_XXS | 10.3 GB | 20.6 t/s | 262K | GOOD FIT | A67 |
Q4_K_M·39.2 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.4 GB | 39.2 t/s | 131K | FAIR FIT | B60 |
Q4_K_M·39.2 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.4 GB | 39.2 t/s | 131K | FAIR FIT | B60 |
Q4_K_M·42.3 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 5.0 GB | 42.3 t/s | 131K | FAIR FIT | B57 |
Q4_K_M·39.0 t/s tok/s·16K ctx·FAIR FIT | Q4_K_M | 5.4 GB | 39.0 t/s | 16K | FAIR FIT | B60 |
Q4_K_M·31.2 t/s tok/s·8K ctx·GOOD FIT | Q4_K_M | 6.8 GB | 31.2 t/s | 8K | GOOD FIT | A72 |
Q4_K_M·36.4 t/s tok/s·4K ctx·FAIR FIT | Q4_K_M | 5.8 GB | 36.4 t/s | 4K | FAIR FIT | B63 |
Q4_K_M·41.4 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 5.1 GB | 41.4 t/s | 33K | FAIR FIT | B58 |
AMD Radeon RX 6700 XT Specifications
- Brand
- AMD
- Architecture
- RDNA 2
- VRAM
- 12.0 GB GDDR6
- Memory Bandwidth
- 384.0 GB/s
- Stream Processors
- 2,560
- FP16 Performance
- 13.20 TFLOPS
- TDP
- 230W
- Release Date
- 2021-03-18
- MSRP
- $479
Get Started
GPUs to Consider Over AMD Radeon RX 6700 XT
Similar GPUs and upgrades with more VRAM or higher bandwidth for AI
NVIDIA GeForce RTX 3090 Ti
NVIDIA · Ampere
NVIDIA GeForce RTX 4090
NVIDIA · Ada Lovelace
AMD Radeon RX 7900 XTX
AMD · RDNA 3
NVIDIA GeForce RTX 5080
NVIDIA · Blackwell
NVIDIA GeForce RTX 3090
NVIDIA · Ampere
NVIDIA GeForce RTX 3080 Ti
NVIDIA · Ampere
Frequently Asked Questions
- Can AMD Radeon RX 6700 XT run Gemma 3 12B IT?
Yes, the AMD Radeon RX 6700 XT with 12 GB can run Gemma 3 12B IT, Gemma 4 12B IT, Llama 2 13B Chat HF, and 1056 other models. 44 models run at excellent quality, and 176 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.
- Is AMD Radeon RX 6700 XT good for AI?
The AMD Radeon RX 6700 XT has 12 GB of GDDR6, making it solid for running local AI models. It supports 220 models at good quality or better. With 384.0 GB/s memory bandwidth, it delivers reasonable token generation speeds. It's a practical entry point — ideal for 7B models like Llama 3 8B and Mistral 7B.
- How many parameters can AMD Radeon RX 6700 XT handle?
With 12 GB, the AMD Radeon RX 6700 XT supports models from 3B to 13B parameters depending on quantization level. At Q4_K_M (the recommended sweet spot), you can fit roughly 20B parameters. 7B models fit well at Q4–Q5, with room for context. Larger 13B models need Q3 or lower.
- What quantization should I use on AMD Radeon RX 6700 XT?
For the best balance of quality and speed on the AMD Radeon RX 6700 XT, start with Q4_K_M — it preserves ~85% of the original model quality while keeping VRAM usage reasonable. If a model barely fits, drop to Q3_K_M — quality loss is noticeable but still useful for chat. Avoid Q2_K unless you just want to test whether a model works at all.
- How fast is AMD Radeon RX 6700 XT for AI inference?
With 384.0 GB/s memory bandwidth, the AMD Radeon RX 6700 XT achieves approximately 47 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~24 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.
tok/s = (384 GB/s ÷ model GB) × efficiency
Smaller models = faster inference. Memory bandwidth is the main bottleneck for token generation speed.
Estimated speed on AMD Radeon RX 6700 XT
~26 tok/s~26 tok/s~25 tok/s~26 tok/sReal-world results typically within ±20%. Speed depends on quantization kernel, batch size, and software stack.
- What's the best model for AMD Radeon RX 6700 XT?
The top-rated models for the AMD Radeon RX 6700 XT are Gemma 3 12B IT, Gemma 4 12B IT, Llama 2 13B Chat HF. The best choice depends on your use case: coding assistants benefit from code-tuned models, while general chat works well with instruction-tuned models like Llama or Qwen.
- What power supply and cooling does AMD Radeon RX 6700 XT need?
The AMD Radeon RX 6700 XT has a TDP of 230 W. A good rule of thumb is to provide at least double the GPU's TDP to cover the rest of the system — that means a 550 W PSU or larger. A mid-tower case with one intake and one rear exhaust is usually sufficient. Keep dust filters clean, as sustained inference generates continuous heat rather than the brief spikes typical of gaming.