# GLM-4.5-Air vs OTel-2.0-LLM-31B-IT (slim)

> GLM-4.5-Air scores 60.3 (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/glm-4-5-air-vs-otel-2-0-llm-31b-it.md (~9,850 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/glm-4-5-air-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/glm-4-5-air-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
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GLM-4.5-Air scores 60.3 (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.

- GLM-4.5-Air: C 60.3, rank #90 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-5-air.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
- GLM-4.5-Air, good for Agents with two to four datacentre GPUs, or a provider account, who want a permissively licensed English and Chinese tool-calling model with wide runtime support. Ahead on Reach, 70 against 50; Risk, 65 against 55; Agent interface, 85 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 38.

| Category | GLM-4.5-Air | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 50 |
| Risk (20%) | 65 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 38 | 74 |

| Fact (where they differ) | GLM-4.5-Air | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | AT&T (Open Telco AI) |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-08-11 | 2026-11-01 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +36: GLM-4.5-Air 38 (Model card 8 of 20, intended use, parameters and languages only.); 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.)
- Agent interface, GLM-4.5-Air +25: GLM-4.5-Air 85 (Chat template 20, a Jinja file 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.)
- Reach, GLM-4.5-Air +20: GLM-4.5-Air 70 (Memory 5 of 30, Z.ai's smallest build is FP8 at 112.6 GB, about 135 GB with a fifth added, too much for our reference machine and within 256 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…)
- Risk, GLM-4.5-Air +10: GLM-4.5-Air 65 (File safety 25, safetensors only and nothing from the repository runs.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)