Xing4.0 29B A4B — Hardware Requirements & GPU Compatibility
Chat
Xing4.0 29B A4B is a 31.2B-parameter open language model from XingChen-AGI. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 20.20 GB of VRAM — see which GPUs and Macs can run it below.
39.0K downloads
1.6K likesSpecifications
- Publisher
- XingChen-AGI
- Parameters
- 31.2B
- Architecture
- Xing4_0ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2026-09-16
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Xing4.0 29B A4B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 14.7 GB | 163.9 GB | 13.27 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 16.7 GB | 165.8 GB | 15.22 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 20.2 GB | 169.3 GB | 18.73 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 23.7 GB | 172.9 GB | 22.24 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 27.2 GB | 176.4 GB | 25.75 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 32.7 GB | 181.8 GB | 31.22 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 63.9 GB | 213.1 GB | 62.43 GB | Brain floating point 16 — preferred for training |
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 Xing4.0 29B A4B?
Q4_K_M · 20.2 GBXing4.0 29B A4B (Q4_K_M) requires 20.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 27+ GB is recommended. Using the full 262K context window can add up to 149.2 GB, bringing total usage to 169.3 GB. 7 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Xing4.0 29B A4B?
Q4_K_M · 20.2 GB41 devices with unified memory can run Xing4.0 29B A4B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Xing4.0 29B A4B need?
Xing4.0 29B A4B requires 20.2 GB of VRAM at Q4_K_M, or 63.9 GB at BF16. Full 262K context adds up to 149.2 GB (169.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 31.2B × 4.8 bits ÷ 8 = 18.7 GB
KV Cache + Overhead ≈ 1.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 150.7 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M20.2 GBQ4_K_M + full context169.3 GB- Can NVIDIA GeForce RTX 4090 run Xing4.0 29B A4B?
Yes, at Q5_K_M (23.7 GB) or lower. Higher quantizations like Q6_K (27.2 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Xing4.0 29B A4B?
For Xing4.0 29B A4B, Q4_K_M (20.2 GB) offers the best balance of quality and VRAM usage. Q5_K_M (23.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 14.7 GB.
VRAM requirement by quantization
Q2_K14.7 GBQ4_K_M ★20.2 GBQ5_K_M23.7 GBQ6_K27.2 GBQ8_032.7 GBBF1663.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Xing4.0 29B A4B on a Mac?
Xing4.0 29B A4B requires at least 14.7 GB at Q2_K, 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 Xing4.0 29B A4B locally?
Yes — Xing4.0 29B A4B can run locally on consumer hardware. At Q4_K_M quantization it needs 20.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Xing4.0 29B A4B?
At Q4_K_M, Xing4.0 29B A4B can reach ~115 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~132 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 ÷ 20.2 × 0.65 = ~347 tok/s
Estimated speed at Q4_K_M (20.2 GB)
~347 tok/s~132 tok/s~347 tok/s~302 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Xing4.0 29B A4B?
At Q4_K_M, the download is about 18.73 GB. The full-precision BF16 version is 62.43 GB. The smallest option (Q2_K) is 13.27 GB.
- Which GPUs can run Xing4.0 29B A4B?
7 consumer GPUs can run Xing4.0 29B A4B at Q4_K_M (20.2 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Xing4.0 29B A4B?
41 devices with unified memory can run Xing4.0 29B A4B at Q4_K_M (20.2 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.