# Hy-Memory-30B-A3B vs OTel-2.0-LLM-31B-IT (slim)

> Hy-Memory-30B-A3B scores 61 (C) to OTel-2.0-LLM-31B-IT's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-otel-2-0-llm-31b-it.md (~10,300 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-otel-2-0-llm-31b-it
- 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 scores 61 (C) on agent readiness against OTel-2.0-LLM-31B-IT's 56.8 (C), and leads in 3 of 4 scored categories. OTel-2.0-LLM-31B-IT leads on documentation and upkeep. 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
- OTel-2.0-LLM-31B-IT: C 56.8, rank #111 of 160 open-weight models · https://www.anchorterminal.com/tools/otel-2-0-llm-31b-it.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 50; Risk, 60 against 55; Agent interface, 65 against 60.
- OTel-2.0-LLM-31B-IT, good for Telecoms teams that want an open model for standards questions and RAG on their own hardware Ahead on Documentation and upkeep, 74 against 68.

| Category | Hy-Memory-30B-A3B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 50 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 65 | 60 |
| Documentation and upkeep (10%) | 68 | 74 |

| Fact (where they differ) | Hy-Memory-30B-A3B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | AT&T (Open Telco AI) |
| Last release | 2026-10-16 | 2026-11-01 |

Why the edge:
- Reach, Hy-Memory-30B-A3B +35: 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.); OTel-2.0-LLM-31B-IT 50 (Memory 10, the publisher's only build is the BF16 safetensors, 62.55 GB for the 15 shards the index names, and 62.55 GB × 1.2 = 75.1 GB, above 64 GB and inside…)
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +6: 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)…); OTel-2.0-LLM-31B-IT 74 (Model card 14, Intended use, a long limitations section, the architecture and training method, the parameters (31B) and the language (English) are on the card.)
- Risk, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)
- Agent interface, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); OTel-2.0-LLM-31B-IT 60 (Chat template 20, chat_template.jinja in the repository, 19,300 characters, the publisher's own.)