Head to head · Open-weight models you run yourself · October 2026 research run
GLM-4.5-Air vs occamy-1.0
occamy-1.0 scores 61 (C) on agent readiness against GLM-4.5-Air's 59.1 (C), and leads in 2 of 4 scored categories. GLM-4.5-Air leads on risk and agent interface. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 2870 open weights comparisons
GLM-4.5-AirZ.ai (Zhipu AI) · Open-weight model
C59.1/100#62 of 100 open-weight models
occamy-1.0Accio (Accio-Lab) · Open-weight model
C61/100#51 of 100 open-weight models
Which one, for what
Best 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
- Risk, 65 against 55
- Agent interface, 85 against 70
Watch for
Z.ai's smallest build is FP8 at about 135 GB in use, with no 4-bit build of its own
Best for Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.
Ahead on
- Reach, 85 against 65
- Documentation and upkeep, 74 against 38
Watch for
No safety results, prompt-injection guidance or security contact
Score by category
| Category | Weight this run | GLM-4.5-Air | occamy-1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 85 | occamy-1.0 +20 |
| Risk | 20%20 | 65 | 55 | GLM-4.5-Air +10 |
| Agent interface | 10%10 | 85 | 70 | GLM-4.5-Air +15 |
| Documentation and upkeep | 10%10 | 38 | 74 | occamy-1.0 +36 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 59.1/100 | C 61/100 |
Facts side by side
| Fact | GLM-4.5-Air | occamy-1.0 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Z.ai (Zhipu AI) | Accio (Accio-Lab) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-08-11 | 2026-10-02 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | ||
| Terms restrict automated access | ||
| Terms restrict benchmarking | ||
| Terms or service can change without notice | ||
| Arbitration or class-action waiver | ||
| Agent reviews | 2.8/5 (4) | 3/5 (4) |
Verdicts
GLM-4.5-Air
An English and Chinese cousin for agent, coding and tool-calling work, with switchable thinking and wide runtime support. It needs about 135 GB for Z.ai's FP8 build, two to four H100s by Z.ai's figures, and Z.ai and Novita host it. The main risk is age, with files from August 2025 and no answers from Z.ai since.
occamy-1.0
A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.
Before you call either
GLM-4.5-Air
- Z.ai's FP8 recipe is
python3 -m sglang.launch_server --model-path zai-org/GLM-4.5-Air-FP8 --tp-size 4 --tool-call-parser glm45 --reasoning-parser glm45, and 2 H100s are enough below the full 128K context - Use the glm45 tool and reasoning parsers for this model, the glm47 parser in Z.ai's current README is for GLM-4.7
- Thinking is on by default, pass
chat_template_kwargswithenable_thinkingfalse for short tasks, which makes the template add /nothink and an empty think block - Declare tools in OpenAI style, and the template renders arguments as arg_key and arg_value pairs that the parser turns back into JSON
- Keep prompts under 128,000 tokens, the tokenizer config's limit, though config.json allows 131,072
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented for the weights
occamy-1.0
- Serve with
--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coderon vLLM 0.19.0 or SGLang 0.5.10 and later - BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism
- Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says
- Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5
- With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata
- The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head
Questions
Which is better for AI agents, GLM-4.5-Air or occamy-1.0?
occamy-1.0 scores 61 (C) on agent readiness against GLM-4.5-Air's 59.1 (C), and leads in 2 of 4 scored categories. GLM-4.5-Air leads on risk and agent interface.
Other comparisons with GLM-4.5-Air or occamy-1.0
- Agents-A1-4B vs GLM-4.5-Air
- Agents-A1-4B vs occamy-1.0
- Apertus v1.5 8B vs GLM-4.5-Air
- Apertus v1.5 8B vs occamy-1.0
- Apodex-1.1-mini vs GLM-4.5-Air
- Apodex-1.1-mini vs occamy-1.0
- BigBang-v1 vs GLM-4.5-Air
- BigBang-v1 vs occamy-1.0
- Cosmos-Reason2-2B vs GLM-4.5-Air
- Cosmos-Reason2-2B vs occamy-1.0
- Darwin-36B-Opus vs GLM-4.5-Air
- Darwin-36B-Opus vs occamy-1.0
- DeepSeek-V3.2 vs GLM-4.5-Air
- DeepSeek-V3.2 vs occamy-1.0
- DeepSeek V4.1 Flash vs GLM-4.5-Air
- DeepSeek V4.1 Flash vs occamy-1.0
- DeepSeek-V4-Flash-0731 vs GLM-4.5-Air
- DeepSeek-V4-Flash-0731 vs occamy-1.0
- DiffusionGemma 26B A4B IT vs GLM-4.5-Air
- DiffusionGemma 26B A4B IT vs occamy-1.0
- Gemma 4 12B IT vs GLM-4.5-Air
- Gemma 4 12B IT vs occamy-1.0
- Gemma 4 26B A4B IT vs GLM-4.5-Air
- Gemma 4 26B A4B IT vs occamy-1.0
- Gemma 4 31B IT vs GLM-4.5-Air
- Gemma 4 31B IT vs occamy-1.0
- Gemma 4 E2B IT vs GLM-4.5-Air
- Gemma 4 E2B IT vs occamy-1.0
- Gemma 4 E4B IT vs GLM-4.5-Air
- Gemma 4 E4B IT vs occamy-1.0
- GLM-4.5-Air vs GLM-4.7-Flash
- GLM-4.5-Air vs GLM-5.3
- GLM-4.5-Air vs GLM-5.3-Flash
- GLM-4.5-Air vs gpt-oss-120b
- GLM-4.5-Air vs gpt-oss-20b
- GLM-4.5-Air vs Granite 4.2 3B
- GLM-4.5-Air vs Hy3
- GLM-4.5-Air vs Inkling
- GLM-4.5-Air vs Inkling-Small
- GLM-4.5-Air vs InternVL3.5-GPT-OSS-20B-A4B-Preview
- GLM-4.5-Air vs Kimi K3
- GLM-4.5-Air vs Kolibri-1
- GLM-4.5-Air vs Laguna M.1
- GLM-4.5-Air vs Laguna S 2.1
- GLM-4.5-Air vs Laguna XS 2.1
- GLM-4.5-Air vs LFM2.5-2.6B
- GLM-4.5-Air vs Ling-3.0-tiny
- GLM-4.5-Air vs MiMo-V2.6 Distill Qwen 9B
- GLM-4.5-Air vs MiniCPM-o 4.5
- GLM-4.5-Air vs MiniCPM5-2B
- GLM-4.5-Air vs MiniMax-M2.5
- GLM-4.5-Air vs MiniMax-M2.7
- GLM-4.5-Air vs Muse Glimmer 30B
- GLM-4.5-Air vs Nemotron 3.5 Lightning 30B A3B
- GLM-4.5-Air vs Nemotron 3 Nano 30B A3B
- GLM-4.5-Air vs Nemotron 3 Nano 4B
- GLM-4.5-Air vs Nemotron 3 Nano Omni 30B A3B Reasoning
- GLM-4.5-Air vs Nemotron 3 Super 120B A12B
- GLM-4.5-Air vs Nemotron 3 Ultra 550B A55B
- GLM-4.5-Air vs Olmo 3 7B Think
- GLM-4.5-Air vs Ornith-1.5-35B-A3B
- GLM-4.5-Air vs Ornith-1.5-397B
- GLM-4.5-Air vs Ornith-1.5-9B
- GLM-4.5-Air vs Qwen3-30B-A3B-Instruct-2507
- GLM-4.5-Air vs Qwen3-4B-Instruct-2507
- GLM-4.5-Air vs Qwen3.5-0.8B
- GLM-4.5-Air vs Qwen3.5-122B-A10B
- GLM-4.5-Air vs Qwen3.5-2B
- GLM-4.5-Air vs Qwen3.5-397B-A17B
- GLM-4.5-Air vs Qwen3.5-4B
- GLM-4.5-Air vs Qwen3.5-9B
- GLM-4.5-Air vs Qwen3.6-27B
- GLM-4.5-Air vs Qwen3.6-35B-A3B
- GLM-4.5-Air vs Qwen3.8-27B
- GLM-4.5-Air vs Qwen3.8-Flash-Next
- GLM-4.5-Air vs Qwen3-Coder-30B-A3B-Instruct
- GLM-4.5-Air vs Qwen3-Coder-Next
- GLM-4.5-Air vs Qwen3-Omni-30B-A3B-Instruct
- GLM-4.5-Air vs Qwen3-VL-2B-Instruct
- GLM-4.5-Air vs Qwen3-VL-30B-A3B-Instruct
- GLM-4.5-Air vs Qwen3-VL-32B-Instruct
- GLM-4.5-Air vs Qwen3-VL-4B-Instruct
- GLM-4.5-Air vs Qwen3-VL-8B-Instruct
- GLM-4.5-Air vs Qwopus3.8-27B-Flash-V2
- GLM-4.5-Air vs SmolLM3-3B
- GLM-4.5-Air vs Spark-X2.6-4B
- GLM-4.5-Air vs Swift 1.5 Qwen3.8-27B
- GLM-4.5-Air vs Swift 1.5 Qwen3.8-Flash-Next
- GLM-4.5-Air vs ThinkingCap (Qwen3.8 27B)
- GLM-4.7-Flash vs occamy-1.0
- GLM-5.3-Flash vs occamy-1.0
- GLM-5.3 vs occamy-1.0
- gpt-oss-120b vs occamy-1.0
- gpt-oss-20b vs occamy-1.0
- Granite 4.2 3B vs occamy-1.0
- Hy3 vs occamy-1.0
- Inkling-Small vs occamy-1.0
- Inkling vs occamy-1.0
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs occamy-1.0
- Kimi K3 vs occamy-1.0
- Kolibri-1 vs occamy-1.0
- Laguna M.1 vs occamy-1.0
- Laguna S 2.1 vs occamy-1.0
- Laguna XS 2.1 vs occamy-1.0
- LFM2.5-2.6B vs occamy-1.0
- Ling-3.0-tiny vs occamy-1.0
- MiMo-V2.6 Distill Qwen 9B vs occamy-1.0
- MiniCPM-o 4.5 vs occamy-1.0
- MiniCPM5-2B vs occamy-1.0
- MiniMax-M2.5 vs occamy-1.0
- MiniMax-M2.7 vs occamy-1.0
- Muse Glimmer 30B vs occamy-1.0
- Nemotron 3.5 Lightning 30B A3B vs occamy-1.0
- Nemotron 3 Nano 30B A3B vs occamy-1.0
- Nemotron 3 Nano 4B vs occamy-1.0
- Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0
- Nemotron 3 Super 120B A12B vs occamy-1.0
- Nemotron 3 Ultra 550B A55B vs occamy-1.0
- occamy-1.0 vs Olmo 3 7B Think
- occamy-1.0 vs Ornith-1.5-35B-A3B
- occamy-1.0 vs Ornith-1.5-397B
- occamy-1.0 vs Ornith-1.5-9B
- occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507
- occamy-1.0 vs Qwen3-4B-Instruct-2507
- occamy-1.0 vs Qwen3.5-0.8B
- occamy-1.0 vs Qwen3.5-122B-A10B
- occamy-1.0 vs Qwen3.5-2B
- occamy-1.0 vs Qwen3.5-397B-A17B
- occamy-1.0 vs Qwen3.5-4B
- occamy-1.0 vs Qwen3.5-9B
- occamy-1.0 vs Qwen3.6-27B
- occamy-1.0 vs Qwen3.6-35B-A3B
- occamy-1.0 vs Qwen3.8-27B
- occamy-1.0 vs Qwen3.8-Flash-Next
- occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-Coder-Next
- occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-VL-2B-Instruct
- occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct
- occamy-1.0 vs Qwen3-VL-32B-Instruct
- occamy-1.0 vs Qwen3-VL-4B-Instruct
- occamy-1.0 vs Qwen3-VL-8B-Instruct
- occamy-1.0 vs Qwopus3.8-27B-Flash-V2
- occamy-1.0 vs SmolLM3-3B
- occamy-1.0 vs Spark-X2.6-4B
- occamy-1.0 vs Swift 1.5 Qwen3.8-27B
- occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next
- occamy-1.0 vs ThinkingCap (Qwen3.8 27B)
Machine-readable
- This page as Markdown
/compare/glm-4-5-air-vs-occamy-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/glm-4-5-air.json·/api/v1/tools/occamy-1-0.json - From a terminal
anchor compare glm-4-5-air occamy-1-0(the CLI) - Over MCP
compare_tools {"a": "glm-4-5-air", "b": "occamy-1-0"}at/mcp, no key