Qwen1.5 MoE A2.7B Chat — Hardware Requirements & GPU Compatibility
Chat
Qwen1.5 MoE A2.7B Chat is a 2.7B-parameter open language model from Alibaba in the Qwen family. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 2.32 GB of VRAM — see which GPUs and Macs can run it below.
30.4K downloads
133 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen
- Parameters
- 2.7B
- Architecture
- Qwen2MoeForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2024-03-14
- License
- Other
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HuggingFace
How Much VRAM Does Qwen1.5 MoE A2.7B Chat Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 1.9 GB | 7.9 GB | 1.15 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 2.0 GB | 8.1 GB | 1.32 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 2.3 GB | 8.4 GB | 1.62 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 2.6 GB | 8.7 GB | 1.92 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 2.9 GB | 9.0 GB | 2.23 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 3.4 GB | 9.4 GB | 2.70 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 6.1 GB | 12.1 GB | 5.40 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 Qwen1.5 MoE A2.7B Chat?
Q4_K_M · 2.3 GBQwen1.5 MoE A2.7B Chat (Q4_K_M) requires 2.3 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 33K context window can add up to 6.0 GB, bringing total usage to 8.4 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Qwen1.5 MoE A2.7B Chat?
Q4_K_M · 2.3 GB59 devices with unified memory can run Qwen1.5 MoE A2.7B Chat, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen1.5 MoE A2.7B Chat need?
Qwen1.5 MoE A2.7B Chat requires 2.3 GB of VRAM at Q4_K_M, or 6.1 GB at BF16. Full 33K context adds up to 6.0 GB (8.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 2.7B × 4.8 bits ÷ 8 = 1.6 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 6.8 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M2.3 GBQ4_K_M + full context8.4 GB- What's the best quantization for Qwen1.5 MoE A2.7B Chat?
For Qwen1.5 MoE A2.7B Chat, Q4_K_M (2.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (2.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.9 GB.
VRAM requirement by quantization
Q2_K1.9 GBQ4_K_M ★2.3 GBQ5_K_M2.6 GBQ6_K2.9 GBQ8_03.4 GBBF166.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen1.5 MoE A2.7B Chat on a Mac?
Qwen1.5 MoE A2.7B Chat requires at least 1.9 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 Qwen1.5 MoE A2.7B Chat locally?
Yes — Qwen1.5 MoE A2.7B Chat can run locally on consumer hardware. At Q4_K_M quantization it needs 2.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen1.5 MoE A2.7B Chat?
At Q4_K_M, Qwen1.5 MoE A2.7B Chat can reach ~1897 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~282 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 ÷ 2.3 × 0.65 = ~2241 tok/s
Estimated speed at Q4_K_M (2.3 GB)
~2241 tok/s~282 tok/s~2241 tok/s~1897 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen1.5 MoE A2.7B Chat?
At Q4_K_M, the download is about 1.62 GB. The full-precision BF16 version is 5.40 GB. The smallest option (Q2_K) is 1.15 GB.
- Which GPUs can run Qwen1.5 MoE A2.7B Chat?
50 consumer GPUs can run Qwen1.5 MoE A2.7B Chat at Q4_K_M (2.3 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 Qwen1.5 MoE A2.7B Chat?
59 devices with unified memory can run Qwen1.5 MoE A2.7B Chat at Q4_K_M (2.3 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.