# Hy-Memory-30B-A3B vs Swift 1.5 Qwen3.8-27B (slim)

> Hy-Memory-30B-A3B and Swift 1.5 Qwen3.8-27B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-swift-1-5-qwen3-8-27b.md (~10,200 tokens) · this version ~880 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-swift-1-5-qwen3-8-27b.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-swift-1-5-qwen3-8-27b
- 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)

Hy-Memory-30B-A3B and Swift 1.5 Qwen3.8-27B score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.

- Hy-Memory-30B-A3B: C 61, rank #68 of 160 open-weight models · https://www.anchorterminal.com/tools/hy-memory-30b-a3b.min.md
- Swift 1.5 Qwen3.8-27B: C 61, rank #57 of 160 open-weight models · https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-27b.min.md
- Hy-Memory-30B-A3B, good for Agents with an external memory framework that want a local model for the write path on a 24 GB card Ahead on Reach, 85 against 80; Risk, 60 against 50; Agent interface, 65 against 60; Documentation and upkeep, 68 against 43.
- Swift 1.5 Qwen3.8-27B, good for Agents on a 24 to 32 GB GPU or Mac that want Qwen3.8-27B's skills with shorter thinking, for teams under US$1M revenue or research.

| Category | Hy-Memory-30B-A3B | Swift 1.5 Qwen3.8-27B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 80 |
| Risk (20%) | 60 | 50 |
| Agent interface (10%) | 65 | 60 |
| Documentation and upkeep (10%) | 68 | 43 |

| Fact (where they differ) | Hy-Memory-30B-A3B | Swift 1.5 Qwen3.8-27B |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | UkisAI |
| Licence | Apache-2.0 | Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue with a separate Swift Enterprise License above it. Built on Qwen3.8-27B, whose Apache 2.0 still governs the base |
| Last release | 2026-10-16 | 2026-09-24 |
| Terms last updated | no document linked | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 2.3/5 (4) |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +25: Hy-Memory-30B-A3B 68 (Model card 8, Intended use (the write path of Mem0, MemOS and Hy-Memory), parameters (30B, about 3B active) and languages (English and Chinese, in the metadata)…); Swift 1.5 Qwen3.8-27B 43 (Model card 8 of 20, intended use, parameters and context only.)
- Risk, Hy-Memory-30B-A3B +10: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); Swift 1.5 Qwen3.8-27B 50 (File safety 25, safetensors only and nothing from the repository runs.)
- Reach, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 85 (Memory 25, Tencent's own Q4_K_M GGUF is 18.24 GB, and 18.24 GB × 1.2 = 21.9 GB, which fits 24 GB but not 16 GB.); Swift 1.5 Qwen3.8-27B 80 (Memory 25 of 30, UkisAI's 4-bit MLX build is 15.9 GB and its 4-bit GGUF with the vision projector 16.4 GB, both under 20 GB with a fifth added, which fits 24 GB…)
- Agent interface, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); Swift 1.5 Qwen3.8-27B 60 (Chat template 20, the base's Jinja file.)