Compare / Nanbeige4.3 33B vs Qwen3 32B
Nanbeige4.3 33B vs Qwen3 32B
Updated November 2026
Verdict
Nanbeige4.3 33B scores higher on the Small LM Index: 77.8 vs 52.4. On the 1 benchmark both labs report, Nanbeige4.3 33B wins 1 and Qwen3 32B wins 0. Both need about 23.2 GB of memory at 4-bit quantization. Only Qwen3 32B has a hosted API on OpenRouter ($0.13 per million tokens); the other has to be self-hosted.
Pick Nanbeige4.3 33B if…
- you want the strongest model overall
- you need math and reasoning
- you work with long documents
Pick Qwen3 32B if…
- you want a hosted API rather than running it yourself
- you want the more widely used model (more quantized builds and community support)
Specifications
| Nanbeige4.3 33B | Qwen3 32B | |
|---|---|---|
| Small LM Index | 77.8 (likely 77–80) | 52.4 (likely 47–57) |
| Lab | Nanbeige (Kanzhun) · China | Alibaba (Qwen) · China |
| Released | 2026-10-24 | 2025-04-29 |
| Parameters | 33.1B (dense) | 32.8B (dense) |
| Memory at 4-bit | ~23 GB | ~23.2 GB |
| Context window | 524K tokens | 131K tokens |
| Input | text | text |
| Reasoning | Always thinks | Hybrid (thinking on/off) |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | Self-host only | $0.13 ($0.080 in, $0.28 out) |
| Hugging Face downloads (30 days) | 17.8K | 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 | Nanbeige4.3 33B | Qwen3 32B |
|---|---|---|
| GPQA Diamond Knowledge | 89.5 | ≈ 66 |
| AIME Math | 95.2 | 72.9 |
| LiveCodeBench Coding | ≈ 89 | 65.7 |
| Terminal-Bench Agentic | 80.9 | — |
| AA-LCR Long context | 84.0 | — |
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, Nanbeige4.3 33B or Qwen3 32B?
Nanbeige4.3 33B scores higher on the Small LM Index: 77.8 vs 52.4. On the 1 benchmark both labs report, Nanbeige4.3 33B wins 1 and Qwen3 32B wins 0.
Which is cheaper to run?
Only Qwen3 32B has a hosted API on OpenRouter ($0.13 per million tokens); the other has to be self-hosted. Both need about 23.2 GB of memory at 4-bit quantization.
Which has the longer context window?
Nanbeige4.3 33B has the longer context window: 524K tokens against 131K.
Can I use Nanbeige4.3 33B and Qwen3 32B 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.