Can I Run Qwen 3.7 on AMD Radeon RX 7900 XTX?
Written by Jakub Rusinowski · Last updated July 12, 2026
Yes, but it's tight — Qwen 3.7 35B-A3B at Q4_K_M needs 23.8 GB at 8K context (21.1 GB weights + 2.7 GB KV cache/overhead), leaving ~0.2 GB of the AMD Radeon RX 7900 XTX's 24 GB, at ~126 tok/s (est.), with room for up to 8K context.
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AMD Radeon RX 7900 XTX Specs
| VRAM | 24 GB |
| Memory Bandwidth | 960 GB/s |
Qwen 3.7 35B-A3B on the AMD Radeon RX 7900 XTX: VRAM by quantization
| Quant | VRAM needed | Fits 24 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 72.7 GB | ✗ No | — | — |
| Q8_0 | 39.9 GB | ✗ No | — | — |
| Q6_K | 31.4 GB | ✗ No | — | — |
| Q5_K_M | 27.5 GB | ✗ No | — | — |
| Q4_K_M | 23.8 GB | ✓ Yes | 8K | — |
| Q3_K_M | 17.6 GB | ✓ Yes | 32K | — |
| Q2_K | 14.2 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 24 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the AMD Radeon RX 7900 XTX: 8K 23.8 GB · 32K 29.4 GB ✗ · 128K 52 GB ✗. Past 32K it no longer fits 24 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Qwen 3.7 35B-A3B on 24 GB of system RAM, CPU only: runs, but it is tight.
Qwen 3.7 Sizes That Fit the AMD Radeon RX 7900 XTX (at 8K context)
| Qwen 3.7 35B-A3B | Q4_K_M · 23.8 GB at 8K context · ~126 tok/s (est.) |
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FAQ
Is the AMD Radeon RX 7900 XTX enough to run Qwen 3.7 locally?
Yes, but it's tight — Qwen 3.7 35B-A3B at Q4_K_M needs 23.8 GB at 8K context (21.1 GB weights + 2.7 GB KV cache/overhead), leaving ~0.2 GB of the AMD Radeon RX 7900 XTX's 24 GB, at ~126 tok/s (est.), with room for up to 8K context.
What's the best Qwen 3.7 size for the AMD Radeon RX 7900 XTX?
Qwen 3.7 35B-A3B at Q4_K_M quantization needs 23.8 GB at 8K context (21.1 GB weights + 2.7 GB KV cache/overhead), estimated ~126 tokens/sec, up to 8K context.
Qwen 3.7 on Other GPUs
- Qwen 3.7 on NVIDIA GeForce RTX 4090
- Qwen 3.7 on NVIDIA GeForce RTX 3090
- Qwen 3.7 on Apple M4 Pro
- Qwen 3.7 on Apple M3
- Qwen 3.7 on Apple M2
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VRAM Tier
Troubleshooting
- Ollama: "model requires more system memory than is available"
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
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