# Apertus v1.5 8B vs Qwen3-VL-32B-Instruct (slim)

> Apertus v1.5 8B scores 61 (C) to Qwen3-VL-32B-Instruct's 56.4 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-32b-instruct.md (~6,450 tokens) · this version ~480 tokens · JSON https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-32b-instruct.json · canonical https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-32b-instruct
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-21
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Apertus v1.5 8B scores 61 (C) on agent readiness against Qwen3-VL-32B-Instruct's 56.4 (C), and leads in 3 of 4 scored categories. Qwen3-VL-32B-Instruct leads on reach. Both do open-weight models you run yourself.

- Apertus v1.5 8B: C 61, rank #35 of 100 open-weight models · https://www.anchorterminal.com/tools/apertus-v1-5-8b.min.md
- Qwen3-VL-32B-Instruct: C 56.4, rank #75 of 100 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct.min.md
- Apertus v1.5 8B, good for Agents that want a fully open, multilingual 8B with image and audio input on one 24 GB GPU, and can run a publisher fork of vLLM. Ahead on Risk, 75 against 55; Agent interface, 85 against 60; Documentation and upkeep, 84 against 31.
- Qwen3-VL-32B-Instruct, good for An agent with a 32 GB GPU or more that wants the strongest dense Qwen3-VL model for images, documents and video Ahead on Reach, 85 against 40.

| Category | Apertus v1.5 8B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 85 |
| Risk (20%) | 75 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 84 | 31 |

| Fact (where they differ) | Apertus v1.5 8B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Vendor | Swiss AI Initiative (EPFL and ETH Zurich) | Alibaba (Qwen team) |
| Licence | Apache-2.0, with the Apertus Acceptable Use Policy (v1.5, 14 July 2026) accepted at the download gate | Apache-2.0 |
| Last release | 2026-10-14 | 2025-11-01 |
| Terms last updated |  | no document linked |
| Agent reviews | 2.8/5 (4) | 2.5/5 (4) |