Baichuan 13B Base — Hardware Requirements & GPU Compatibility
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Baichuan 13B Base is a 13B-parameter open language model from baichuan-inc in the Baichuan family. At Q4_K_M it needs about 8.58 GB of VRAM — see which GPUs and Macs can run it below.
467 downloads
187 likesSpecifications
- Publisher
- baichuan-inc
- Family
- Baichuan
- Parameters
- 13B
- Architecture
- BaichuanForCausalLM
- Vocabulary Size
- 64,000
- Release Date
- 2023-07-08
Get Started
HuggingFace
How Much VRAM Does Baichuan 13B Base Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 6.1 GB | — | 5.53 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 7.0 GB | — | 6.34 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 8.6 GB | — | 7.80 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 10.2 GB | — | 9.26 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 11.8 GB | — | 10.72 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 14.3 GB | — | 13.00 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 28.6 GB | — | 26.00 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 Baichuan 13B Base?
Q4_K_M · 8.6 GBBaichuan 13B Base (Q4_K_M) requires 8.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 12+ GB is recommended. 39 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 Baichuan 13B Base?
Q4_K_M · 8.6 GB49 devices with unified memory can run Baichuan 13B Base, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Baichuan 13B Base
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Baichuan 13B Base need?
Baichuan 13B Base requires 8.6 GB of VRAM at Q4_K_M, or 28.6 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 13B × 4.8 bits ÷ 8 = 7.8 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M8.6 GB- Can NVIDIA GeForce RTX 4090 run Baichuan 13B Base?
Yes, at Q8_0 (14.3 GB) or lower. Higher quantizations like BF16 (28.6 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Baichuan 13B Base?
For Baichuan 13B Base, Q4_K_M (8.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (10.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 6.1 GB.
VRAM requirement by quantization
Q2_K6.1 GBQ4_K_M ★8.6 GBQ5_K_M10.2 GBQ6_K11.8 GBQ8_014.3 GBBF1628.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Baichuan 13B Base on a Mac?
Baichuan 13B Base requires at least 6.1 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 Baichuan 13B Base locally?
Yes — Baichuan 13B Base can run locally on consumer hardware. At Q4_K_M quantization it needs 8.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Baichuan 13B Base?
At Q4_K_M, Baichuan 13B Base can reach ~513 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~76 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 ÷ 8.6 × 0.65 = ~606 tok/s
Estimated speed at Q4_K_M (8.6 GB)
~606 tok/s~76 tok/s~606 tok/s~513 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Baichuan 13B Base?
At Q4_K_M, the download is about 7.80 GB. The full-precision BF16 version is 26.00 GB. The smallest option (Q2_K) is 5.53 GB.
- Which GPUs can run Baichuan 13B Base?
39 consumer GPUs can run Baichuan 13B Base at Q4_K_M (8.6 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Baichuan 13B Base?
52 devices with unified memory can run Baichuan 13B Base at Q4_K_M (8.6 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.