Compare / Phi-4 vs LLaDA2.2 mini
Phi-4 vs LLaDA2.2 mini
Updated November 2026
Verdict
Phi-4 scores higher on the Small LM Index: 44.7 vs 29.7. On the 1 benchmark both labs report, Phi-4 wins 1 and LLaDA2.2 mini wins 0. Both need about 11.4 GB of memory at 4-bit quantization. Only Phi-4 has a hosted API on OpenRouter ($0.070 per million tokens); the other has to be self-hosted.
Pick Phi-4 if…
- you want the strongest model overall
- you want a hosted API rather than running it yourself
- you want the more widely used model (more quantized builds and community support)
Pick LLaDA2.2 mini if…
- you work with long documents
Specifications
| Phi-4 | LLaDA2.2 mini | |
|---|---|---|
| Small LM Index | 44.7 (likely 35–55) | 29.7 (likely 26–34) |
| Lab | Microsoft (Phi) · United States | InclusionAI (Ling) · China |
| Released | 2024-12-12 | 2026-09-05 |
| Parameters | 14.7B (dense) | 16.3B (1.4B active, MoE) |
| Memory at 4-bit | ~11.4 GB | ~11 GB |
| Context window | 16K tokens | 131K tokens |
| Input | text | text |
| Reasoning | No thinking | No thinking |
| License | MIT | Apache-2.0 |
| API price / 1M tokens | $0.070 ($0.056 in, $0.11 out) | Self-host only |
| Hugging Face downloads (30 days) | 327K | 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 | Phi-4 | LLaDA2.2 mini |
|---|---|---|
| MMLU-Pro Knowledge | 70.4 | ≈ 57 |
| GPQA Diamond Knowledge | 56.1 | 44.4 |
| AIME Math | ≈ 61 | 35.1 |
| LiveCodeBench Coding | ≈ 50 | 28.1 |
| τ²-Bench Agentic | — | 57.5 |
| IFBench Instruction following | — | 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, Phi-4 or LLaDA2.2 mini?
Phi-4 scores higher on the Small LM Index: 44.7 vs 29.7. On the 1 benchmark both labs report, Phi-4 wins 1 and LLaDA2.2 mini wins 0.
Which is cheaper to run?
Only Phi-4 has a hosted API on OpenRouter ($0.070 per million tokens); the other has to be self-hosted. Both need about 11.4 GB of memory at 4-bit quantization.
Which has the longer context window?
LLaDA2.2 mini has the longer context window: 131K tokens against 16K.
Can I use Phi-4 and LLaDA2.2 mini commercially?
Phi-4 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.