Compare / Qwen3.5 9B vs Apertus 1.5 8B
Qwen3.5 9B vs Apertus 1.5 8B
Updated November 2026
Verdict
Qwen3.5 9B scores higher on the Small LM Index: 63.9 vs 20.1. On the 2 benchmarks both labs report, Qwen3.5 9B wins 2 and Apertus 1.5 8B wins 0. Both need about 7.2 GB of memory at 4-bit quantization. Only Qwen3.5 9B has a hosted API on OpenRouter ($0.028 per million tokens); the other has to be self-hosted.
Pick Qwen3.5 9B 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 Apertus 1.5 8B if…
No clear advantage in the data we have.
Specifications
| Qwen3.5 9B | Apertus 1.5 8B | |
|---|---|---|
| Small LM Index | 63.9 (likely 58–69) | 20.1 (likely 15–28) |
| Lab | Alibaba (Qwen) · China | Swiss AI Initiative (Apertus) · Europe |
| Released | 2026-03-02 | 2026-07-24 |
| Parameters | 9B (dense) | 8.9B (dense) |
| Memory at 4-bit | ~6.4 GB | ~7.2 GB |
| Context window | 262K tokens | 262K tokens |
| Input | text, image, video | text, image, audio |
| Reasoning | Hybrid (thinking on/off) | Hybrid (thinking on/off) |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | $0.028 ($0.025 in, $0.036 out) | Self-host only |
| Hugging Face downloads (30 days) | 6.4M | 42K |
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 | Qwen3.5 9B | Apertus 1.5 8B |
|---|---|---|
| MMLU-Pro Knowledge | 82.5 | 48.8 |
| GPQA Diamond Knowledge | 81.7 | 27.2 |
| LiveCodeBench Coding | 65.6 | ≈ 20 |
| τ²-Bench Agentic | 79.1 | — |
| IFBench Instruction following | 64.5 | — |
| MMMU-Pro Vision | 69.2✓ | — |
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, Qwen3.5 9B or Apertus 1.5 8B?
Qwen3.5 9B scores higher on the Small LM Index: 63.9 vs 20.1. On the 2 benchmarks both labs report, Qwen3.5 9B wins 2 and Apertus 1.5 8B wins 0.
Which is cheaper to run?
Only Qwen3.5 9B has a hosted API on OpenRouter ($0.028 per million tokens); the other has to be self-hosted. Both need about 7.2 GB of memory at 4-bit quantization.
Which has the longer context window?
Both have a 262K-token context window.
Can I use Qwen3.5 9B and Apertus 1.5 8B 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.