# Apertus v1.5 8B vs Ling-3.1-flash-1019 (slim)

> Apertus v1.5 8B scores 61 (C) to Ling-3.1-flash-1019's 54.8 (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-ling-3-1-flash-1019.md (~10,250 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019.json · canonical https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- 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 Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach. Both do open-weight models you run yourself.

- Apertus v1.5 8B: C 61, rank #40 of 160 open-weight models · https://www.anchorterminal.com/tools/apertus-v1-5-8b.min.md
- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.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 45; Agent interface, 85 against 60; Documentation and upkeep, 84 against 56.
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding Ahead on Reach, 60 against 40.

| Category | Apertus v1.5 8B | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 60 |
| Risk (20%) | 75 | 45 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 84 | 56 |

| Fact (where they differ) | Apertus v1.5 8B | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Vendor | Swiss AI Initiative (EPFL and ETH Zurich) | inclusionAI (Ant Group) |
| Licence | Apache-2.0, with the Apertus Acceptable Use Policy (v1.5, 14 July 2026) accepted at the download gate | MIT |
| Last release | 2026-10-14 | 2026-11-04 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Risk, Apertus v1.5 8B +30: Apertus v1.5 8B 75 (File safety 25, safetensors only and no code in the repository.); Ling-3.1-flash-1019 45 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the…)
- Documentation and upkeep, Apertus v1.5 8B +28: Apertus v1.5 8B 84 (Model card 14 of 20, languages and a knowledge cut-off are missing.); Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…)
- Agent interface, Apertus v1.5 8B +25: Apertus v1.5 8B 85 (Chat template 20, a Jinja file in the repository.); Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.)
- Reach, Ling-3.1-flash-1019 +20: Apertus v1.5 8B 40 (Memory 25 of 30, the BF16 files are 18.4 GB, or 22.1 GB with a fifth added, which fits 24 GB.); Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.)