Nanbeige4.1 3B — Hardware Requirements & GPU Compatibility
Chat
Nanbeige4.1 3B is a compact chat model from Nanbeige, a Chinese AI startup focused on building efficient small-scale language models. At just under 4 billion parameters, it is designed to run on virtually any modern GPU or even on CPU, making it one of the more accessible options for users with limited hardware. Despite its small size, it handles basic conversation, simple reasoning, and Chinese-English bilingual tasks, serving as a practical entry point for local LLM experimentation.
27.7K downloads
1.1K likesSpecifications
- Publisher
- Nanbeige
- Parameters
- 3.9B
- Architecture
- LlamaForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 166,144
- Release Date
- 2026-02-10
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Nanbeige4.1 3B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 2.1 GB | 19.1 GB | 1.67 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 2.2 GB | 19.2 GB | 1.72 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 2.4 GB | 19.4 GB | 1.92 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 2.8 GB | 19.8 GB | 2.36 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 3.2 GB | 20.3 GB | 2.80 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 3.7 GB | 20.7 GB | 3.25 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 4.4 GB | 21.4 GB | 3.93 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 Nanbeige4.1 3B?
Q4_K_M · 2.8 GBNanbeige4.1 3B (Q4_K_M) requires 2.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 4+ GB is recommended. Using the full 262K context window can add up to 17.1 GB, bringing total usage to 19.8 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Nanbeige4.1 3B?
Q4_K_M · 2.8 GB59 devices with unified memory can run Nanbeige4.1 3B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomWhere to Download Nanbeige4.1 3B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Nanbeige4.1 3B need?
Nanbeige4.1 3B requires 2.8 GB of VRAM at Q4_K_M, or 8.3 GB at BF16. Full 262K context adds up to 17.1 GB (19.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 3.9B × 4.8 bits ÷ 8 = 2.4 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 17.4 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M2.8 GBQ4_K_M + full context19.8 GB- What's the best quantization for Nanbeige4.1 3B?
For Nanbeige4.1 3B, Q4_K_M (2.8 GB) offers the best balance of quality and VRAM usage. Q5_K_S (3.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 2.1 GB.
VRAM requirement by quantization
Q2_K2.1 GBQ3_K_L2.5 GBQ4_K_M ★2.8 GBQ5_K_S3.1 GBQ5_K_M3.2 GBBF168.3 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Nanbeige4.1 3B on a Mac?
Nanbeige4.1 3B requires at least 2.1 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 Nanbeige4.1 3B locally?
Yes — Nanbeige4.1 3B can run locally on consumer hardware. At Q4_K_M quantization it needs 2.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nanbeige4.1 3B?
At Q4_K_M, Nanbeige4.1 3B can reach ~1577 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~235 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 ÷ 2.8 × 0.65 = ~1864 tok/s
Estimated speed at Q4_K_M (2.8 GB)
~1864 tok/s~235 tok/s~1864 tok/s~1577 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nanbeige4.1 3B?
At Q4_K_M, the download is about 2.36 GB. The full-precision BF16 version is 7.87 GB. The smallest option (Q2_K) is 1.67 GB.
- Which GPUs can run Nanbeige4.1 3B?
50 consumer GPUs can run Nanbeige4.1 3B at Q4_K_M (2.8 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Nanbeige4.1 3B?
59 devices with unified memory can run Nanbeige4.1 3B at Q4_K_M (2.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.