ERNIE 4.5 21B A3B PT — Hardware Requirements & GPU Compatibility
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ERNIE 4.5 21B A3B PT is a 21B-parameter open language model from Baidu. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 13.02 GB of VRAM — see which GPUs and Macs can run it below.
25.6K downloads
165 likesSpecifications
- Publisher
- Baidu
- Parameters
- 21B
- Architecture
- Ernie4_5_MoeForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 103,424
- Release Date
- 2025-11-26
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does ERNIE 4.5 21B A3B PT Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 9.3 GB | 16.7 GB | 8.93 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 9.6 GB | 17 GB | 9.19 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 10.7 GB | 18.1 GB | 10.24 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 10.9 GB | 18.3 GB | 10.50 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 13.0 GB | 20.4 GB | 12.60 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 15.4 GB | 22.8 GB | 14.96 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 17.7 GB | 25.1 GB | 17.32 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 21.4 GB | 28.8 GB | 21.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run ERNIE 4.5 21B A3B PT?
Q4_K_M · 13.0 GBERNIE 4.5 21B A3B PT (Q4_K_M) requires 13.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 17+ GB is recommended. Using the full 131K context window can add up to 7.4 GB, bringing total usage to 20.4 GB. 17 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 ERNIE 4.5 21B A3B PT?
Q4_K_M · 13.0 GB27 devices with unified memory can run ERNIE 4.5 21B A3B PT, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Derivatives (2)
Frequently Asked Questions
- How much VRAM does ERNIE 4.5 21B A3B PT need?
ERNIE 4.5 21B A3B PT requires 13.0 GB of VRAM at Q4_K_M, or 21.4 GB at Q8_0. Full 131K context adds up to 7.4 GB (20.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 21B × 4.8 bits ÷ 8 = 12.6 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 7.8 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M13.0 GBQ4_K_M + full context20.4 GB- What's the best quantization for ERNIE 4.5 21B A3B PT?
For ERNIE 4.5 21B A3B PT, Q4_K_M (13.0 GB) offers the best balance of quality and VRAM usage. Q4_K_L (13.3 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 6.2 GB.
VRAM requirement by quantization
IQ2_XXS6.2 GBQ2_K9.3 GBQ3_K_L11.2 GBQ4_K_M ★13.0 GBQ4_K_L13.3 GBQ8_021.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run ERNIE 4.5 21B A3B PT on a Mac?
ERNIE 4.5 21B A3B PT requires at least 6.2 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 ERNIE 4.5 21B A3B PT locally?
Yes — ERNIE 4.5 21B A3B PT can run locally on consumer hardware. At Q4_K_M quantization it needs 13.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is ERNIE 4.5 21B A3B PT?
At Q4_K_M, ERNIE 4.5 21B A3B PT can reach ~224 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~50 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 ÷ 13.0 × 0.55 = ~224 tok/s
Estimated speed at Q4_K_M (13.0 GB)
~224 tok/s~50 tok/s~167 tok/s~138 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of ERNIE 4.5 21B A3B PT?
At Q4_K_M, the download is about 12.60 GB. The full-precision Q8_0 version is 21.00 GB. The smallest option (IQ2_XXS) is 5.78 GB.
- Which GPUs can run ERNIE 4.5 21B A3B PT?
17 consumer GPUs can run ERNIE 4.5 21B A3B PT at Q4_K_M (13.0 GB). Top options include AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, AMD Radeon RX 6800. 6 GPUs have plenty of headroom for comfortable inference.
- Which devices can run ERNIE 4.5 21B A3B PT?
27 devices with unified memory can run ERNIE 4.5 21B A3B PT at Q4_K_M (13.0 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.