Hunyuan A13B Instruct — Hardware Requirements & GPU Compatibility
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Hunyuan A13B Instruct is a 80.4B-parameter open language model from Tencent in the Hunyuan family. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 48.80 GB of VRAM — see which GPUs and Macs can run it below.
51.2K downloads
795 likesSpecifications
- Publisher
- Tencent
- Family
- Hunyuan
- Parameters
- 80.4B
- Architecture
- HunYuanMoEV1ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 128,167
- Release Date
- 2025-06-25
- License
- Other
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HuggingFace
How Much VRAM Does Hunyuan A13B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 34.7 GB | 38.8 GB | 34.17 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 35.7 GB | 39.8 GB | 35.17 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 39.8 GB | 43.8 GB | 39.19 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 40.8 GB | 44.8 GB | 40.20 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 48.8 GB | 52.8 GB | 48.24 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 57.9 GB | 61.9 GB | 57.28 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 66.9 GB | 70.9 GB | 66.32 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 81.0 GB | 85.0 GB | 80.39 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Hunyuan A13B Instruct?
Q4_K_M · 48.8 GBHunyuan A13B Instruct (Q4_K_M) requires 48.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 64+ GB is recommended. Using the full 33K context window can add up to 4.0 GB, bringing total usage to 52.8 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hunyuan A13B Instruct?
Q4_K_M · 48.8 GB22 devices with unified memory can run Hunyuan A13B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Where to Download Hunyuan A13B Instruct
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 Hunyuan A13B Instruct need?
Hunyuan A13B Instruct requires 48.8 GB of VRAM at Q4_K_M, or 161.3 GB at BF16. Full 33K context adds up to 4.0 GB (52.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 80.4B × 4.8 bits ÷ 8 = 48.2 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.6 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M48.8 GBQ4_K_M + full context52.8 GB- Can NVIDIA GeForce RTX 4090 run Hunyuan A13B Instruct?
Yes, at IQ2_XXS (22.7 GB) or lower. Higher quantizations like IQ2_M (27.7 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Hunyuan A13B Instruct?
For Hunyuan A13B Instruct, Q4_K_M (48.8 GB) offers the best balance of quality and VRAM usage. Q5_K_S (55.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 22.7 GB.
VRAM requirement by quantization
IQ2_XXS22.7 GBIQ3_M36.8 GBIQ4_XS43.8 GBQ4_K_M ★48.8 GBQ5_K_S55.8 GBBF16161.3 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hunyuan A13B Instruct on a Mac?
Hunyuan A13B Instruct requires at least 22.7 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 Hunyuan A13B Instruct locally?
Yes — Hunyuan A13B Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 48.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hunyuan A13B Instruct?
At Q4_K_M, Hunyuan A13B Instruct can reach ~124 tok/s on AMD Instinct MI350X. 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 ÷ 48.8 × 0.65 = ~305 tok/s
Estimated speed at Q4_K_M (48.8 GB)
~305 tok/s~305 tok/s~236 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hunyuan A13B Instruct?
At Q4_K_M, the download is about 48.24 GB. The full-precision BF16 version is 160.79 GB. The smallest option (IQ2_XXS) is 22.11 GB.
- Which GPUs can run Hunyuan A13B Instruct?
No single consumer GPU has enough VRAM to run Hunyuan A13B Instruct at Q4_K_M (48.8 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hunyuan A13B Instruct?
23 devices with unified memory can run Hunyuan A13B Instruct at Q4_K_M (48.8 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (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.