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GPU guide for 4-bit LLMs VRAM tiers and performance

Compare budget, mid, high and extreme GPUs for 4-bit models, VRAM requirements and token-per-second benchmarks.

1. Budget tier, 8 GB to 12 GB VRAM

GPU VRAM (GB) Bandwidth (GB/s)
RTX 4060 8 272
RTX 5060 8 448
RX 7600 8 288
RTX 3060 12 360
RTX 4070 / 4070 Super 12 504
RX 7700 XT 12 432
Arc B580 12 456

These cards can run 4-bit quantized models that require up to roughly 8 GB of VRAM, such as many 7 B-parameter LLMs. Models larger than 12 GB generally need a card with more memory.

2. Mid tier, 16 GB VRAM

GPU VRAM (GB) Bandwidth (GB/s) Example speed*
RTX 4060 Ti 16 288 n/a
RTX 4070 Ti Super 16 672 n/a
RTX 4080 Super 16 736 n/a
RTX 5060 Ti 16 448 111 t/s (gpt-oss-20b MXFP4)
RTX 5070 Ti 16 896 n/a
RX 7800 XT 16 624 n/a
RX 9070 XT 16 640 137 t/s (Llama 2 7B Q4_0)
RX 9060 XT 16 322 n/a

*Speed figures are taken directly from the benchmark data.

These cards can accommodate most 20-B-parameter models quantized to 4-bit. The measured speeds show the impact of bandwidth: the RTX 5060 Ti (448 GB/s) achieved 111 t/s on gpt-oss-20b, while the RX 9070 XT (640 GB/s) reached 137 t/s on the smaller Llama 2 7B, so the two figures are not directly comparable.

3. High tier, 24 GB to 32 GB VRAM

GPU VRAM (GB) Bandwidth (GB/s) Example speed*
RTX 3090 24 936 162 t/s (gpt-oss-20b MXFP4)
RTX 3090 Ti 24 1008 n/a
RTX 4090 24 1008 198 t/s (Qwen3-30B-A3B Q4_K_M)
RTX 5090 32 1792 247 t/s (Qwen3-30B-A3B Q4_K_M)
RX 7900 XTX 24 960 140 t/s (GLM-4.7-Flash Q4_0)

*Speed figures are taken directly from the benchmark data.

These GPUs can run 30-B-parameter models at 4-bit. The RTX 4090 and RTX 5090 show higher token-per-second rates than the RTX 3090.

4. Extreme tier, 48 GB to 96 GB VRAM

GPU VRAM (GB) Bandwidth (GB/s)
RTX A6000 48 768
RTX 6000 Ada 48 960
RTX PRO 6000 Blackwell 96 1792

These professional cards provide the largest memory capacities available for home-lab setups. They are required for the biggest 4-bit models that exceed 48 GB.

5. Unified-memory systems

System Unified memory (GB) Usable for model (≈ 75 %) Bandwidth (GB/s)
Mac mini M4 Pro 64 ~48 273
Mac M4 Max 128 ~96 546
Mac Studio M3 Ultra 512 ~384 819
Ryzen AI Max+ 395 128 ~96 256
NVIDIA DGX Spark 128 ~96 273

The DGX Spark achieved 83 t/s on gpt-oss-20b MXFP4, comparable to mid-range NVIDIA GPUs.

Choosing the right GPU

  1. Model size: 4-bit 20-B-parameter models need about 12 GB VRAM; 30-B models need about 24 GB.
  2. Memory match: For ≤12 GB, budget cards such as RTX 3060 work. For 24 GB models, select RTX 4090, RTX 3090, or RX 7900 XTX.
  3. Speed considerations: Higher bandwidth generally yields higher token-per-second rates, as shown by the benchmark numbers.
  4. Budget: RTX 5060 Ti offers a 16 GB solution with measured 111 t/s on a 20-B model, while RX 9070 XT provides 137 t/s on a 7-B model.

Quick reference

Tier Typical VRAM Example GPUs Example token-per-second (20 B model)
Budget 8-12 GB RTX 3060, RTX 4060 n/a
Mid 16 GB RTX 5060 Ti, RX 9070 XT 111 (RTX 5060 Ti)
High 24-32 GB RTX 4090, RTX 3090 162 to 225
Extreme 48 GB+ RTX A6000, RTX PRO 6000 n/a (handles the largest 4-bit models)
Unified 64-512 GB Mac Studio M3 Ultra, DGX Spark 83 to 116 (bandwidth dependent)
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