# Nanbeige4.3-33B vs occamy-1.0

> Nanbeige4.3-33B and occamy-1.0 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.

- Canonical: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0
- Markdown: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0.md (~6,400 tokens)
- Slim: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-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: 2026-10-25

Nanbeige4.3-33B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep. Both do open-weight models you run yourself.

- Nanbeige4.3-33B: grade C, 61/100, rank #56 of 111 open-weight models. Markdown https://www.anchorterminal.com/tools/nanbeige-4-3-33b.md · JSON https://www.anchorterminal.com/api/v1/tools/nanbeige-4-3-33b.json
- occamy-1.0: grade C, 61/100, rank #55 of 111 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 3341 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Nanbeige4.3-33B (C)

Good for: Agents with about 96 GB of GPU memory, or the 128 GB reference machine, that want an Apache-tagged 33B model for long coding and tool loops and can wait for independent results.

Ahead on:
- Risk, 60 against 55
- Agent interface, 85 against 70

Watch for: No independent benchmark result yet; every agentic number on the card is Nanbeige's own run

### 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 55
- Documentation and upkeep, 74 against 56

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


## Score by category

| Category | Weight | Nanbeige4.3-33B | occamy-1.0 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 55 | 85 | occamy-1.0 +30 |
| Risk | 20% (20 this run) | 60 | 55 | Nanbeige4.3-33B +5 |
| Agent interface | 10% (10 this run) | 85 | 70 | Nanbeige4.3-33B +15 |
| Documentation and upkeep | 10% (10 this run) | 56 | 74 | occamy-1.0 +18 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Nanbeige4.3-33B | occamy-1.0 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Nanbeige LLM Lab (BOSS Zhipin) | Accio (Accio-Lab) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-24 | 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 | none | 3/5 (4) |

## Verdicts

**Nanbeige4.3-33B.** A dense 33B Llama-architecture cousin for long agentic coding and office tasks, with per-request thinking, XML tool calls that stock vLLM and SGLang parse, and 512K of context. It needs about 96 GB at BF16, as Nanbeige ships no quantised build. Its agentic results so far are Nanbeige's own, with no safety results, training data notes or licence file.

**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

### Nanbeige4.3-33B

1. Serve with `vllm serve Nanbeige/Nanbeige4.3-33B --enable-auto-tool-choice --reasoning-parser qwen3 --tool-call-parser qwen3_coder`, as the card says, or SGLang with the same two parsers
2. Keep `tool_call_format` at its default `xml`, since qwen3_coder parses that format; the `json` option writes Hermes-style JSON calls, which need a different parser such as vLLM's hermes
3. Pass `chat_template_kwargs` `{"preserve_thinking": true}` for multi-turn tool use and coding, and `{"enable_thinking": false}` to skip reasoning, as the card recommends
4. Use temperature 1.0, top_p 0.95 and up to 65,536 new tokens for agent work, and temperature 0.6 for reasoning and chat, per the card
5. Send your own system prompt, since without one the template injects a Chinese identity line, or a Chinese tool-expert prompt when tools are passed
6. Send one system message at the start only, as the template raises an error for a later one
7. In plain Transformers pass `use_cache=True` to generate, since config.json and generation_config.json set it false; trust_remote_code isn't needed

### 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, Nanbeige4.3-33B or occamy-1.0?

Nanbeige4.3-33B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nanbeige-4-3-33b", "b": "occamy-1-0"}`. From a terminal: `anchor compare nanbeige-4-3-33b occamy-1-0`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/nanbeige-4-3-33b.json and https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json

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- [Nanbeige4.3-33B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-8-27b.md)
- [Nanbeige4.3-33B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-8-flash-next.md)
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- [Nanbeige4.3-33B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-vl-2b-instruct.md)
- [Nanbeige4.3-33B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-vl-30b-a3b-instruct.md)
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- [Nanbeige4.3-33B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-vl-4b-instruct.md)
- [Nanbeige4.3-33B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-vl-8b-instruct.md)
- [Nanbeige4.3-33B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwopus3-8-27b-flash-v2.md)
- [Nanbeige4.3-33B vs Recursive Flint](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-recursive-flint.md)
- [Nanbeige4.3-33B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-smollm3-3b.md)
- [Nanbeige4.3-33B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-spark-x2-6-4b.md)
- [Nanbeige4.3-33B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-swift-1-5-qwen3-8-27b.md)
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- [Nanbeige4.3-33B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.md)
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- [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)
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- [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)
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- [occamy-1.0 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.md)
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- [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)
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- [occamy-1.0 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next.md)
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- [occamy-1.0 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.md)
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- [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 Recursive Flint](https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint.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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