All compatibility checks

Compatibility check

Can you run Qwen2.5 Coder 32B Instruct on the Radeon RX 9070 XT?

Not on a single card

Not on a single Radeon RX 9070 XT. Even at 4-bit, Qwen2.5 Coder 32B Instruct needs about 19.8 GB, which exceeds the card's 16 GB. You would need roughly 2× Radeon RX 9070 XT with tensor parallelism, a larger GPU, or a smaller model.

Memory breakdown

Weights plus a 1 GB KV cache at 4,096tokens, against the card's 16 GB. Verdicts leave ~10% headroom for activations and fragmentation.

PrecisionWeightsKV cacheTotal% of 16 GBFit
FP16 / BF16full quality75.3 GB1 GB76.3 GB477%No
INT8 (8-bit)near-full quality37.7 GB1 GB38.7 GB242%No
INT4 (4-bit)GPTQ / AWQ / GGUF Q418.8 GB1 GB19.8 GB124%No

Planning estimates, not a substitute for profiling. Real usage varies with the inference runtime, batch size, and how much context you actually use — the KV cache grows linearly with prompt length.

GPUs that run Qwen2.5 Coder 32B Instruct

Cards where this model fits (at its best precision):

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Frequently asked questions

Can the Radeon RX 9070 XT run Qwen2.5 Coder 32B Instruct?

No. Even 4-bit needs about 19.8 GB, more than the 16 GB available.

How much VRAM does Qwen2.5 Coder 32B Instruct need?

Approximately 75.3 GB in FP16, 37.7 GB in INT8, and 18.8 GB in 4-bit for the weights, plus a KV cache of about 1 GB at 4,096 tokens.

Does quantization let Qwen2.5 Coder 32B Instruct fit on the Radeon RX 9070 XT?

Not on a single Radeon RX 9070 XT — even 4-bit exceeds 16 GB. You would need multiple GPUs or a larger card.

What happens to memory with longer context?

The KV cache grows linearly with prompt length. At 4,096 tokens it is about 1 GB here; doubling the context roughly doubles that term, so long-context use can push a tight fit over the edge.