Best local LLM for radeon rx 7900 xt
Last updated 2026-05-26 · Page updated 2026-07-13
Top 7 open-source picks for radeon rx 7900 xt, ranked by benchmark performance and real-world fit. Updated monthly.
gpt-oss 20B
OpenAI's compact open-weight MoE with 3.6B active out of 21B total parameters. Matches o3-mini on a laptop-class GPU under Apache 2.0.
ERNIE 4.5 21B-A3B Thinking
Baidu's compact reasoning MoE with 3B active parameters out of 21B total. Fast inference thanks to the small active set, with Chinese-language strength.
LLaDA 2.0 Uni 16B
Ant Group's first open Apache 2.0 diffusion LLM: a 16B/1B MoE paired with a 6.2B diffusion decoder, unifying text and vision generation and editing. Released April 2026.
Mistral Small 3
Mistral AI's 24B dense model that closes most of the gap with 70B-class models. Best quality-per-parameter we've measured at this size in 2025.
Mistral Small 3.1 24B
Mistral AI's Small 3.1 — Small 3 plus a vision encoder, a 128k context, and ~150 tok/s inference under Apache 2.0. Small 3.2 (June 2025) is a drop-in upgrade.
Devstral Small 2 24B
Mistral AI's 24B coding specialist co-developed with All Hands AI, scoring 72.2% on SWE-Bench under Apache 2.0. Fits on a single RTX 4090.
Mistral Small 3.2 24B
Mistral AI's June 2025 refresh of Small 3.1: a 24B Apache 2.0 dense model with vision input, sharper function calling, and roughly half the rate of runaway generations seen in 3.1.
Which GPU should you buy to run gpt-oss 20B?
To run gpt-oss 20B locally at Q4, you need ~13 GB of VRAM. The best value for this is a RTX 5070 Ti (16 GB VRAM).
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Frequently asked questions
What is the best local LLM for radeon rx 7900 xt?
gpt-oss 20B tops this ranking — a 21B model, licensed under Apache 2.0, needing about 13 GB of VRAM at Q4 quantization. See the full list below for the runner-ups and how they compare.
How much VRAM do I need to run gpt-oss 20B?
At Q4 quantization, gpt-oss 20B needs about 13 GB of VRAM and fits comfortably on a single 24 GB GPU.
Which of these models fit an 16 GB GPU?
At Q4 quantization, gpt-oss 20B, ERNIE 4.5 21B-A3B Thinking, Mistral Small 3, Mistral Small 3.1 24B, Devstral Small 2 24B and 1 more fit within 16 GB of VRAM.
Are the models on this radeon rx 7900 xt list free for commercial use?
Licenses across this list include Apache 2.0. Check the specific license of each model on its catalog page before deploying commercially, as terms vary by author.
What context window do these models support?
Context windows on this list range from 8k to 250k tokens, depending on the model.