Can the Radeon RX 9070 XT Run Llama 3.2 1B?

Runs

Yes. Llama 3.2 1B at Q4_K_M is a 0.8 GB download (Hugging Face file listing for bartowski/Llama-3.2-1B-Instruct-GGUF), and the Radeon RX 9070 XT has 16 GB of VRAM, leaving about 15.2 GB for the KV cache and runtime. No published speed measurement for this pair passes SpecPicks' sanity checks yet, so no tokens-per-second figure is quoted.

Model file0.8 GBQ4_K_M

VRAM16 GBRadeon RX 9070 XT

Headroom15.2 GBafter weights

Median speed—0 cited runs

Bandwidth ceiling~796 tok/s645 GB/s ÷ 0.8 GB

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Published runs for Llama 3.2 1B on the Radeon RX 9070 XT

No published run for this pair has passed the checks yet.

More about this pair

How much VRAM does Llama 3.2 1B need?

The Q4_K_M file is 0.8 GB. Add roughly 1.5 GB for the runtime and an ~8K-token context, so about 2.3 GB of VRAM holds it comfortably. Longer contexts grow the KV cache and need more.

What is the fastest Llama 3.2 1B can generate on the Radeon RX 9070 XT?

Generation reads every weight once per token, so the Radeon RX 9070 XT's 645 GB/s of memory bandwidth divided by the 0.8 GB file sets a ceiling near 796 tokens per second. Real runs land below it; SpecPicks rejects any published figure above it.

Check another pair

See the full matrix → · All Radeon RX 9070 XT benchmarks →

Llama 3.2 1B on other GPUs

RTX 4060 — Runs
RTX 3060 Ti — Runs
RTX 3060 12GB — Runs, 184 tok/s median
Intel Arc B580 — Runs
RTX 4070 SUPER — Runs, 183 tok/s median
RTX 4060 Ti 16GB — Runs, 209 tok/s median
RTX 5060 Ti 16GB — Runs, 210 tok/s median
Intel Arc A770 16GB — Runs
RTX 4070 Ti SUPER — Runs, 161 tok/s median
RTX 4080 — Runs
RTX 5070 Ti — Runs, 185 tok/s median
RTX 5080 — Runs, 103 tok/s median
RTX 3090 — Runs, 267 tok/s median
Radeon RX 7900 XTX — Runs, 106 tok/s median
RTX 4090 — Runs
RTX 5090 — Runs
RTX A6000 48GB — Runs
RTX PRO 6000 Blackwell 96GB — Runs, 244 tok/s median

Other models on the Radeon RX 9070 XT

Llama 3.2 3B — Runs
Mistral 7B — Runs
Qwen2.5 7B — Runs
Llama 3.1 8B — Runs
DeepSeek-R1-Distill-Llama 8B — Runs
Qwen3 8B — Runs, 90 tok/s median
Gemma 2 9B — Runs
Gemma 3 12B — Runs
Qwen2.5 14B — Runs
DeepSeek-R1-Distill-Qwen 14B — Runs
Qwen3 14B — Runs, 50.1 tok/s median
Phi-4 14B — Runs
gpt-oss-20b — Runs, 91.9 tok/s median
Gemma 3 27B — Offload
Gemma 2 27B — Offload
Qwen3 30B-A3B — Offload
Qwen3 32B — Offload
Qwen2.5 32B — Offload
DeepSeek-R1-Distill-Qwen 32B — Offload
Llama 3.1 70B — Offload
Llama 3.3 70B — Offload
DeepSeek-R1-Distill-Llama 70B — Offload

How the checks work

The fit is the Q4_K_M file size against the card's VRAM, with 1.5 GB kept for the runtime and an ~8K context. A published run counts only if the pair fits, the run is Q4-class, its source does not call it an estimate, it is under the bandwidth ceiling above, and it is not one figure pasted across many cards. The whole matrix is downloadable as a CSV under CC BY 4.0.

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This page is editorial synthesis based on publicly available information. No independent first-party benchmarking is reported.