Leaderboard / InclusionAI (Ling)
Ling-mini-2.0
InclusionAI (Ling) · Ling 2.0 · released 2025-09-09 · data checked 2026-11-01 Needs verification
Ling-mini-2.0 is a 16.3B-parameter Mixture-of-Experts model (1.4B active per token) from InclusionAI (Ling) (China), released 2025-09-09 under the MIT license. It doesn't have enough reported benchmarks for an index score yet. It needs about 11 GB of memory at 4-bit with an 8K-token context.
Benchmarks
Each bar shows this model's score. The tick marks the best medium model on that benchmark.
No benchmark results for this release yet. Know of one? Send it.
Specifications
- Lab
- InclusionAI (Ling) (CN · China)
- Architecture
- Mixture-of-Experts
- Total parameters
- 16.3B
- Active parameters
- 1.4B
- Size class
- Medium
- Context window
- 128K tokens
- Input modalities
- text
- Reasoning
- Instruct (no thinking)
- License
- MIT
- Openness
- Open weights
- Memory to run
- ~11 GB at 4-bit, 8K context (more sizes)
- Hugging Face
- 4.6K downloads (30 days) · 208 likes
Compare with
- Ling-mini-2.0 vs LLaDA2.2 mini (16.3B, index 29.7)
- Ling-mini-2.0 vs Apriel 1.6 15B Thinker (14.9B, index 60.9)
- Ling-mini-2.0 vs Phi-4-reasoning-plus (14.7B, index 54.4)
Sources
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Run it locally
Uses inclusionAI/Ling-mini-2.0-GGUF (Q4_K_M). Swap the tag for another size: BF16, Q2_K, Q4_K_M, Q6_K, Q8_0.
ollama run hf.co/inclusionAI/Ling-mini-2.0-GGUF:Q4_K_Mllama-server -hf inclusionAI/Ling-mini-2.0-GGUF:Q4_K_Mpip install -U mlx-lm
mlx_lm.chat --model mlx-community/Ling-mini-2.0-4bitvllm serve inclusionAI/Ling-mini-2.0Memory needed: weights, context cache and runtime buffers.
| Quantization | 4K context | 32K context | 128K context |
|---|---|---|---|
| 16-bit F16 | 34 GB | 35 GB | 39 GB |
| 8-bit Q8_0 | 18 GB | 19 GB | 23 GB |
| 4-bit Q4_K_M | 11 GB | 12 GB | 16 GB |