Compare / Nanbeige4.2 3B vs Gemma 4 E2B
Nanbeige4.2 3B vs Gemma 4 E2B
Updated November 2026
Verdict
Nanbeige4.2 3B scores higher on the Small LM Index: 70.4 vs 31.9. On the 2 benchmarks both labs report, Nanbeige4.2 3B wins 2 and Gemma 4 E2B wins 0. Both need about 3.8 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Nanbeige4.2 3B if…
- you want the strongest model overall
- you mostly write code
- you work with long documents
Pick Gemma 4 E2B if…
- you need image input
- you want the more widely used model (more quantized builds and community support)
Specifications
| Nanbeige4.2 3B | Gemma 4 E2B | |
|---|---|---|
| Small LM Index | 70.4 (likely 69–72) | 31.9 (likely 28–36) |
| Lab | Nanbeige (Kanzhun) · China | Google · United States |
| Released | 2026-07-21 | 2026-04-02 |
| Parameters | 4.2B (dense) | 5.1B (dense) |
| Memory at 4-bit | ~3.8 GB | ~3.7 GB |
| Context window | 262K tokens | 128K tokens |
| Input | text | text, image, audio |
| Reasoning | Always thinks | Hybrid (thinking on/off) |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 120.3K | 3.3M |
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 | Nanbeige4.2 3B | Gemma 4 E2B |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 85 | 60.0 |
| GPQA Diamond Knowledge | 87.4 | 43.4 |
| Humanity's Last Exam Reasoning | 17.8 | ≈ 3 |
| AIME Math | ≈ 93 | 37.5 |
| LiveCodeBench Coding | 72.5 | 44.0 |
| SWE-bench Verified Coding | 63.6 | ≈ 13 |
| Terminal-Bench Agentic | 44.1 | — |
| τ²-Bench Agentic | — | 24.5 |
| MMMU-Pro Vision | — | 44.2 |
| HMMT Math | 82.8 | — |
| AA-LCR Long context | 58.7 | — |
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, Nanbeige4.2 3B or Gemma 4 E2B?
Nanbeige4.2 3B scores higher on the Small LM Index: 70.4 vs 31.9. On the 2 benchmarks both labs report, Nanbeige4.2 3B wins 2 and Gemma 4 E2B wins 0.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 3.8 GB of memory at 4-bit quantization.
Which has the longer context window?
Nanbeige4.2 3B has the longer context window: 262K tokens against 128K.
Can I use Nanbeige4.2 3B and Gemma 4 E2B commercially?
Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.