# GLM-4.7-Flash vs occamy-1.0

> GLM-4.7-Flash scores 63 (B) to occamy-1.0's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0
- Markdown: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.md (~5,850 tokens)
- Slim: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

GLM-4.7-Flash scores 63 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 1 of 4 scored categories. occamy-1.0 leads on reach and documentation and upkeep. Both do open-weight models you run yourself.

- GLM-4.7-Flash: grade B, 63/100, rank #26 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-4-7-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-4-7-flash.json
- occamy-1.0: grade C, 61/100, rank #51 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/occamy-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### GLM-4.7-Flash (B)

Good for: Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime

Ahead on:
- Agent interface, 85 against 70

Watch for: No change to the files since 29 January 2026 and no zai-org reply on discussions since 31 January

### occamy-1.0 (C)

Good 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 80
- Documentation and upkeep, 74 against 28

Watch for: No safety results, prompt-injection guidance or security contact


## Score by category

| Category | Weight | GLM-4.7-Flash | occamy-1.0 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 80 | 85 | occamy-1.0 +5 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 85 | 70 | GLM-4.7-Flash +15 |
| Documentation and upkeep | 10% (10 this run) | 28 | 74 | occamy-1.0 +46 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **63 · B** | **61 · C** | |

## Facts side by side

| Fact | GLM-4.7-Flash | 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 | 2026-01-29 | 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-4.7-Flash.** A small MIT-licensed mixture-of-experts model with about 3B active parameters, for local agent and coding work with several tool calls per turn and optional thinking. It runs in Ollama at about 23 GB and in nearly every common runtime. The main risk is neglect, with no changes or replies since early February and no safety results.

**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-4.7-Flash

1. On our reference machine start it with `vllm serve zai-org/GLM-4.7-Flash --max-model-len 65536 --tool-call-parser glm47 --reasoning-parser glm45 --enable-auto-tool-choice --served-model-name glm-4.7-flash`
2. Or run `ollama run glm-4.7-flash` for the 19 GB q4_K_M build
3. Without the glm47 and glm45 parsers, tool calls and reasoning come back as plain text
4. Use a released vLLM (0.32.0 or later) or SGLang (0.5.22 or later); the card's nightly and pull-request builds date from January 2026
5. Pass `chat_template_kwargs: {"enable_thinking": false}` for short tasks, since thinking is on by default
6. Set `clear_thinking: false` to keep earlier reasoning in multi-turn agent work, as Z.ai does for τ²-Bench and Terminal Bench
7. Set the context length yourself, since config.json allows 202,752 tokens and tokenizer_config.json says 128,000

### occamy-1.0

1. Serve with `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on vLLM 0.19.0 or SGLang 0.5.10 and later
2. BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism
3. Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says
4. Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5
5. With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata
6. 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-4.7-Flash or occamy-1.0?

GLM-4.7-Flash scores 63 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 1 of 4 scored categories. occamy-1.0 leads on reach and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "glm-4-7-flash", "b": "occamy-1-0"}`. From a terminal: `anchor compare glm-4-7-flash occamy-1-0`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/glm-4-7-flash.json and https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json

## Other comparisons with GLM-4.7-Flash or occamy-1.0

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- [Kolibri-1 vs occamy-1.0](https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.md)
- [Laguna M.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.md)
- [Laguna S 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.md)
- [Laguna XS 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.md)
- [LFM2.5-2.6B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0.md)
- [Ling-3.0-tiny vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.md)
- [MiMo-V2.6 Distill Qwen 9B vs occamy-1.0](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.md)
- [MiniCPM-o 4.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.md)
- [MiniCPM5-2B vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.md)
- [MiniMax-M2.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.md)
- [MiniMax-M2.7 vs occamy-1.0](https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0.md)
- [Muse Glimmer 30B vs occamy-1.0](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0.md)
- [Nemotron 3.5 Lightning 30B A3B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0.md)
- [Nemotron 3 Nano 30B A3B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0.md)
- [Nemotron 3 Nano 4B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0.md)
- [Nemotron 3 Super 120B A12B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0.md)
- [Nemotron 3 Ultra 550B A55B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0.md)
- [occamy-1.0 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think.md)
- [occamy-1.0 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b.md)
- [occamy-1.0 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b.md)
- [occamy-1.0 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b.md)
- [occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507.md)
- [occamy-1.0 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.md)
- [occamy-1.0 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b.md)
- [occamy-1.0 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b.md)
- [occamy-1.0 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b.md)
- [occamy-1.0 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b.md)
- [occamy-1.0 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b.md)
- [occamy-1.0 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b.md)
- [occamy-1.0 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.md)
- [occamy-1.0 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b.md)
- [occamy-1.0 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b.md)
- [occamy-1.0 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next.md)
- [occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct.md)
- [occamy-1.0 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next.md)
- [occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct.md)
- [occamy-1.0 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2.md)
- [occamy-1.0 vs SmolLM3-3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.md)
- [occamy-1.0 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b.md)
- [occamy-1.0 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b.md)
- [occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next.md)
- [occamy-1.0 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b.md)

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