Compare / Ling-mini-2.0 vs LLaDA2.2 mini
Ling-mini-2.0 vs LLaDA2.2 mini
Updated November 2026
Verdict
Ling-mini-2.0 scores higher on the Small LM Index: 43.0 vs 36.2. On the 5 benchmarks both labs report, Ling-mini-2.0 wins 3 and LLaDA2.2 mini wins 2. Both need about 11 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Ling-mini-2.0 if…
- you want the strongest model overall
- you mostly write code
- you need math and reasoning
Pick LLaDA2.2 mini if…
- you need precise instruction following
- you build agents that call tools
- you work with long documents
Specifications
| Ling-mini-2.0 | LLaDA2.2 mini | |
|---|---|---|
| Small LM Index | 43.0 (likely 40–46) | 36.2 (likely 33–39) |
| Lab | InclusionAI (Ling) · China | InclusionAI (Ling) · China |
| Released | 2025-09-09 | 2026-09-05 |
| Parameters | 16.3B (1.4B active, MoE) | 16.3B (1.4B active, MoE) |
| Memory at 4-bit | ~11 GB | ~11 GB |
| Context window | 128K tokens | 131K tokens |
| Input | text | text |
| Reasoning | No thinking | No thinking |
| License | MIT | Apache-2.0 |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 4.6K | 4K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Ling-mini-2.0 | LLaDA2.2 mini |
|---|---|---|
| MMLU-Pro Knowledge | 67.1✓ | ≈ 60 |
| GPQA Diamond Knowledge | 56.2✓ | 44.4 |
| Humanity's Last Exam Reasoning | 5.1✓ | ≈ 6 |
| AIME Math | 49.3✓ | 35.1 |
| LiveCodeBench Coding | 42.9✓ | 28.1 |
| τ²-Bench Agentic | 13.2✓ | 57.5 |
| IFBench Instruction following | 23.6✓ | 24.9 |
| BFCL Agentic | — | 47.7 |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Ling-mini-2.0 or LLaDA2.2 mini?
Ling-mini-2.0 scores higher on the Small LM Index: 43.0 vs 36.2. On the 5 benchmarks both labs report, Ling-mini-2.0 wins 3 and LLaDA2.2 mini wins 2.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 11 GB of memory at 4-bit quantization.
Which has the longer context window?
LLaDA2.2 mini has the longer context window: 131K tokens against 128K.
Can I use Ling-mini-2.0 and LLaDA2.2 mini commercially?
Ling-mini-2.0 is released under MIT and LLaDA2.2 mini under Apache-2.0. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.