GPT Neox 20B — Hardware Requirements & GPU Compatibility
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GPT Neox 20B is a 20.7B-parameter open language model from EleutherAI. It supports a context window of up to 2,048 tokens. At Q4_K_M it needs about 13.69 GB of VRAM — see which GPUs and Macs can run it below.
649.3K downloads
584 likesSpecifications
- Publisher
- EleutherAI
- Parameters
- 20.7B
- Architecture
- GPTNeoXForCausalLM
- Context Length
- 2,048 tokens
- Vocabulary Size
- 50,432
- Release Date
- 2022-04-07
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does GPT Neox 20B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 9.7 GB | — | 8.81 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 10.0 GB | — | 9.07 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 11.1 GB | — | 10.11 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 11.4 GB | — | 10.37 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 13.7 GB | — | 12.44 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 16.3 GB | — | 14.78 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 18.8 GB | — | 17.11 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 22.8 GB | — | 20.74 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run GPT Neox 20B?
Q4_K_M · 13.7 GBGPT Neox 20B (Q4_K_M) requires 13.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 18+ GB is recommended. 26 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run GPT Neox 20B?
Q4_K_M · 13.7 GB47 devices with unified memory can run GPT Neox 20B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomWhere to Download GPT Neox 20B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Frequently Asked Questions
- How much VRAM does GPT Neox 20B need?
GPT Neox 20B requires 13.7 GB of VRAM at Q4_K_M, or 45.6 GB at FP16.
VRAM = Weights + KV Cache + Overhead
Weights = 20.7B × 4.8 bits ÷ 8 = 12.4 GB
KV Cache + Overhead ≈ 1.3 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M13.7 GB- Can NVIDIA GeForce RTX 4090 run GPT Neox 20B?
Yes, at Q8_0 (22.8 GB) or lower. Higher quantizations like FP16 (45.6 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for GPT Neox 20B?
For GPT Neox 20B, Q4_K_M (13.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (15.7 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 6.3 GB.
VRAM requirement by quantization
IQ2_XXS6.3 GBIQ3_XS9.4 GBQ3_K_M11.1 GBQ4_K_M ★13.7 GBQ5_K_S15.7 GBFP1645.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run GPT Neox 20B on a Mac?
GPT Neox 20B requires at least 6.3 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run GPT Neox 20B locally?
Yes — GPT Neox 20B can run locally on consumer hardware. At Q4_K_M quantization it needs 13.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is GPT Neox 20B?
At Q4_K_M, GPT Neox 20B can reach ~321 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~48 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 13.7 × 0.65 = ~380 tok/s
Estimated speed at Q4_K_M (13.7 GB)
~380 tok/s~48 tok/s~380 tok/s~321 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of GPT Neox 20B?
At Q4_K_M, the download is about 12.44 GB. The full-precision FP16 version is 41.48 GB. The smallest option (IQ2_XXS) is 5.70 GB.
- Which GPUs can run GPT Neox 20B?
26 consumer GPUs can run GPT Neox 20B at Q4_K_M (13.7 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 7 GPUs have plenty of headroom for comfortable inference.
- Which devices can run GPT Neox 20B?
49 devices with unified memory can run GPT Neox 20B at Q4_K_M (13.7 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.