# Laguna XS 2.1 vs ThinkingCap (Qwen3.8 27B)

> Laguna XS 2.1 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/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b
- Markdown: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.md (~6,550 tokens)
- Slim: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/laguna-xs-2-1-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: 2026-10-21

Laguna XS 2.1 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 documentation and upkeep. Both do open-weight models you run yourself.

- Laguna XS 2.1: grade C, 61/100, rank #40 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-xs-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json
- ThinkingCap (Qwen3.8 27B): grade C, 61/100, rank #50 of 100 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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Laguna XS 2.1 (C)

Good for: Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.

Ahead on:
- Reach, 85 against 75
- Risk, 55 against 45
- Agent interface, 85 against 70

Watch for: No reply from Poolside to any discussion, including reports about the tokenizer and remote code

### 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:
- Documentation and upkeep, 53 against 46

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


## Score by category

| Category | Weight | Laguna XS 2.1 | ThinkingCap (Qwen3.8 27B) | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 85 | 75 | Laguna XS 2.1 +10 |
| Risk | 20% (20 this run) | 55 | 45 | Laguna XS 2.1 +10 |
| Agent interface | 10% (10 this run) | 85 | 70 | Laguna XS 2.1 +15 |
| Documentation and upkeep | 10% (10 this run) | 46 | 53 | ThinkingCap (Qwen3.8 27B) +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Laguna XS 2.1 | ThinkingCap (Qwen3.8 27B) |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Poolside | BottleCap AI |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | OpenMDW-1.1 | PolyForm-Small-Business-1.0.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-19 | 2026-10-06 |
| Terms last updated |  | no document linked |
| Privacy policy last updated |  |  |
| 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) | 2.5/5 (4) |

## Verdicts

**Laguna XS 2.1.** A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.

**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

### Laguna XS 2.1

1. Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF
2. On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)
3. With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds
4. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{"enable_thinking": true}'`, which Poolside recommends for agentic coding
5. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped
6. Sampling per the card is temperature 1.0 and top_k 20
7. The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships
8. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented

### 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, Laguna XS 2.1 or ThinkingCap (Qwen3.8 27B)?

Laguna XS 2.1 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 documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "laguna-xs-2-1", "b": "thinkingcap-qwen3-8-27b"}`. From a terminal: `anchor compare laguna-xs-2-1 thinkingcap-qwen3-8-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json and https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.json

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