Ling Mini 2.0 — Hardware Requirements & GPU Compatibility
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Ling Mini 2.0 is a 16.3B-parameter open language model from Inclusion AI. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 10.14 GB of VRAM — see which GPUs and Macs can run it below.
38.6K downloads
195 likesSpecifications
- Publisher
- Inclusion AI
- Parameters
- 16.3B
- Architecture
- BailingMoeV2ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 157,184
- Release Date
- 2025-09-08
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does Ling Mini 2.0 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 7.3 GB | 8.6 GB | 6.91 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 8.3 GB | 9.6 GB | 7.92 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 10.1 GB | 11.4 GB | 9.75 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 12.0 GB | 13.2 GB | 11.58 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 13.8 GB | 15.1 GB | 13.41 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 16.6 GB | 17.9 GB | 16.26 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 32.9 GB | 34.1 GB | 32.51 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 Ling Mini 2.0?
Q4_K_M · 10.1 GBLing Mini 2.0 (Q4_K_M) requires 10.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 14+ GB is recommended. Using the full 33K context window can add up to 1.3 GB, bringing total usage to 11.4 GB. 27 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 Ling Mini 2.0?
Q4_K_M · 10.1 GB27 devices with unified memory can run Ling Mini 2.0, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomFrequently Asked Questions
- How much VRAM does Ling Mini 2.0 need?
Ling Mini 2.0 requires 10.1 GB of VRAM at Q4_K_M, or 32.9 GB at BF16. Full 33K context adds up to 1.3 GB (11.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 16.3B × 4.8 bits ÷ 8 = 9.8 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 1.6 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M10.1 GBQ4_K_M + full context11.4 GB- Can NVIDIA GeForce RTX 4090 run Ling Mini 2.0?
Yes, at Q8_0 (16.6 GB) or lower. Higher quantizations like BF16 (32.9 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Ling Mini 2.0?
For Ling Mini 2.0, Q4_K_M (10.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (12.0 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 7.3 GB.
VRAM requirement by quantization
Q2_K7.3 GBQ4_K_M ★10.1 GBQ5_K_M12.0 GBQ6_K13.8 GBQ8_016.6 GBBF1632.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Ling Mini 2.0 on a Mac?
Ling Mini 2.0 requires at least 7.3 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 Ling Mini 2.0 locally?
Yes — Ling Mini 2.0 can run locally on consumer hardware. At Q4_K_M quantization it needs 10.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Ling Mini 2.0?
At Q4_K_M, Ling Mini 2.0 can reach ~288 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~65 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 ÷ 10.1 × 0.55 = ~288 tok/s
Estimated speed at Q4_K_M (10.1 GB)
~288 tok/s~65 tok/s~215 tok/s~178 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Ling Mini 2.0?
At Q4_K_M, the download is about 9.75 GB. The full-precision BF16 version is 32.51 GB. The smallest option (Q2_K) is 6.91 GB.
- Which GPUs can run Ling Mini 2.0?
27 consumer GPUs can run Ling Mini 2.0 at Q4_K_M (10.1 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Ling Mini 2.0?
27 devices with unified memory can run Ling Mini 2.0 at Q4_K_M (10.1 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.