XVERSE MoE A4.2B — Hardware Requirements & GPU Compatibility
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XVERSE MoE A4.2B is a 4.2B-parameter open language model from xverse. It supports a context window of up to 8,192 tokens. At BF16 it needs about 9.24 GB of VRAM — see which GPUs and Macs can run it below.
22 downloads
14 likesSpecifications
- Publisher
- xverse
- Parameters
- 4.2B
- Architecture
- XverseForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 100,534
- Release Date
- 2024-04-26
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does XVERSE MoE A4.2B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 9.2 GB | — | 8.40 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run XVERSE MoE A4.2B?
BF16 · 9.2 GBXVERSE MoE A4.2B (BF16) requires 9.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 13+ GB is recommended. 28 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run XVERSE MoE A4.2B?
BF16 · 9.2 GB27 devices with unified memory can run XVERSE MoE A4.2B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does XVERSE MoE A4.2B need?
XVERSE MoE A4.2B requires 9.2 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 4.2B × 16 bits ÷ 8 = 8.4 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF169.2 GB- Can I run XVERSE MoE A4.2B on a Mac?
XVERSE MoE A4.2B requires at least 9.2 GB at BF16, 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 XVERSE MoE A4.2B locally?
Yes — XVERSE MoE A4.2B can run locally on consumer hardware. At BF16 quantization it needs 9.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is XVERSE MoE A4.2B?
At BF16, XVERSE MoE A4.2B can reach ~316 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~71 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 9.2 × 0.55 = ~316 tok/s
Estimated speed at BF16 (9.2 GB)
~316 tok/s~71 tok/s~236 tok/s~195 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of XVERSE MoE A4.2B?
At BF16, the download is about 8.40 GB.
- Which GPUs can run XVERSE MoE A4.2B?
28 consumer GPUs can run XVERSE MoE A4.2B at BF16 (9.2 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run XVERSE MoE A4.2B?
27 devices with unified memory can run XVERSE MoE A4.2B at BF16 (9.2 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.