# Nanbeige4.3-33B vs ThinkingCap (Qwen3.8 27B)

> Nanbeige4.3-33B and ThinkingCap 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-thinkingcap-qwen3-8-27b
- Markdown: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.md (~7,050 tokens)
- Slim: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.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 ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on reach. 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
- ThinkingCap (Qwen3.8 27B): grade C, 61/100, rank #54 of 111 open-weight models. Markdown https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.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 45
- Agent interface, 85 against 70

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

### ThinkingCap (Qwen3.8 27B) (C)

Good for: Small teams and individuals running Qwen3.8-27B for agent or reasoning work who want shorter thinking traces on one 24 GB GPU or Mac.

Ahead on:
- Reach, 75 against 55

Watch for: PolyForm Small Business licence, free commercially only below 100 people and 1,000,000 USD (2019) revenue


## Score by category

| Category | Weight | Nanbeige4.3-33B | ThinkingCap (Qwen3.8 27B) | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 55 | 75 | ThinkingCap (Qwen3.8 27B) +20 |
| Risk | 20% (20 this run) | 60 | 45 | Nanbeige4.3-33B +15 |
| Agent interface | 10% (10 this run) | 85 | 70 | Nanbeige4.3-33B +15 |
| Documentation and upkeep | 10% (10 this run) | 56 | 53 | Nanbeige4.3-33B +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Nanbeige4.3-33B | ThinkingCap (Qwen3.8 27B) |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Nanbeige LLM Lab (BOSS Zhipin) | BottleCap AI |
| 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) | PolyForm-Small-Business-1.0.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-24 | 2026-10-06 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | 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 | 2.5/5 (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.

**ThinkingCap (Qwen3.8 27B).** A Qwen3.8-27B with shorter reasoning, for agent work where thinking tokens cost time, and BottleCap's 4-bit GGUF runs in about 19 GB. The main limits are the licence, which needs a paid licence above 100 people or 1,000,000 USD revenue, a gated main repository, and no safety results or training-data description.

## 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

### ThinkingCap (Qwen3.8 27B)

1. Check the licence first, an organisation with 100 or more people or 1,000,000 USD (2019) revenue needs a commercial licence from BottleCap
2. For files without the gate use `llama-server -hf bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF:Q4_K_M --jinja`, about 17.4 GB
3. On vLLM use `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_xml`, and on SGLang `--tool-call-parser qwen3_coder`
4. Set `reasoning_effort` (xhigh, medium or low) in chat_template_kwargs, any other value makes the template raise an error
5. Keep the base's sampling (temperature 1.0, top_p 0.95, top_k 20), the GGUF card says greedy decoding can loop
6. The GGUFs carry an MTP head, and llama.cpp builds without MTP support for this architecture may refuse to load them with a missing blk.64 tensor

## Questions

### Which is better for AI agents, Nanbeige4.3-33B or ThinkingCap (Qwen3.8 27B)?

Nanbeige4.3-33B and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on reach.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-thinkingcap-qwen3-8-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nanbeige-4-3-33b", "b": "thinkingcap-qwen3-8-27b"}`. From a terminal: `anchor compare nanbeige-4-3-33b thinkingcap-qwen3-8-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/nanbeige-4-3-33b.json and https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.json

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- [Nanbeige4.3-33B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-5-0-8b.md)
- [Nanbeige4.3-33B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-5-122b-a10b.md)
- [Nanbeige4.3-33B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-5-2b.md)
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- [Nanbeige4.3-33B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-5-4b.md)
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- [Nanbeige4.3-33B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-6-27b.md)
- [Nanbeige4.3-33B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-6-35b-a3b.md)
- [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-Coder-Next](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-coder-next.md)
- [Nanbeige4.3-33B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-omni-30b-a3b-instruct.md)
- [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)
- [Nanbeige4.3-33B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-vl-32b-instruct.md)
- [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)
- [Nanbeige4.3-33B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-swift-1-5-qwen3-8-flash-next.md)
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- [Nemotron 3.5 Lightning 30B A3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-thinkingcap-qwen3-8-27b.md)
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- [Nemotron 3 Nano 4B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-thinkingcap-qwen3-8-27b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-thinkingcap-qwen3-8-27b.md)
- [Nemotron 3 Super 120B A12B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-thinkingcap-qwen3-8-27b.md)
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- [occamy-1.0 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b.md)
- [Olmo 3 7B Think vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b.md)
- [Ornith-1.5-35B-A3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-thinkingcap-qwen3-8-27b.md)
- [Ornith-1.5-397B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-thinkingcap-qwen3-8-27b.md)
- [Ornith-1.5-9B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-4B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-0.8B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-122B-A10B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-2B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-397B-A17B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-4B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-9B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.6-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.6-35B-A3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-thinkingcap-qwen3-8-27b.md)
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- [Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-Coder-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-Coder-Next vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-Omni-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.md)
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- [Qwen3-VL-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.md)
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- [Qwen3-VL-4B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3-VL-8B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-thinkingcap-qwen3-8-27b.md)
- [Qwopus3.8-27B-Flash-V2 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-thinkingcap-qwen3-8-27b.md)
- [Recursive Flint vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/recursive-flint-vs-thinkingcap-qwen3-8-27b.md)
- [SmolLM3-3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/smollm3-3b-vs-thinkingcap-qwen3-8-27b.md)
- [Spark-X2.6-4B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-thinkingcap-qwen3-8-27b.md)
- [Swift 1.5 Qwen3.8-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-thinkingcap-qwen3-8-27b.md)
- [Swift 1.5 Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.md)

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