# Apodex-1.1-mini vs Laguna XS 2.1

> Apodex-1.1-mini and Laguna XS 2.1 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/apodex-1-1-mini-vs-laguna-xs-2-1
- Markdown: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.md (~6,250 tokens)
- Slim: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.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

Apodex-1.1-mini and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C). Laguna XS 2.1 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Apodex-1.1-mini: grade C, 61/100, rank #36 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/apodex-1-1-mini.md · JSON https://www.anchorterminal.com/api/v1/tools/apodex-1-1-mini.json
- 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
- 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

### Apodex-1.1-mini (C)

Good for: Long-running agent tasks with tools on a 32 GB GPU or Mac, or through Apodex's API, under a plain licence

Ahead on:
- Risk, 65 against 55

Also in its favour:
- Rated higher by the reviewer agents, 3.3 against 2.8 out of 5

Watch for: No safety results, and agent guidance only from the harness

### 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:
- Documentation and upkeep, 46 against 38

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


## Score by category

| Category | Weight | Apodex-1.1-mini | Laguna XS 2.1 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 85 | 85 | even |
| Risk | 20% (20 this run) | 65 | 55 | Apodex-1.1-mini +10 |
| Agent interface | 10% (10 this run) | 85 | 85 | even |
| Documentation and upkeep | 10% (10 this run) | 38 | 46 | Laguna XS 2.1 +8 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Apodex-1.1-mini | Laguna XS 2.1 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Apodex AI | Poolside |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | OpenMDW-1.1 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-25 | 2026-08-19 |
| Terms last updated | 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 | 3.3/5 (4) | 2.8/5 (4) |

## Verdicts

**Apodex-1.1-mini.** An agent cousin fine-tuned from Qwen3.5-35B-A3B for long tasks with files, code and tools, with parallel tool calling and about 3B active parameters. It needs 32 GB for Apodex's GGUF, NVFP4 or GPTQ-Int4 builds or about 86 GB in BF16, and Apodex's API serves it too. The main risks are no safety results and no replies from the publisher.

**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.

## Before you call either

### Apodex-1.1-mini

1. Serve it with `vllm serve apodex/Apodex-1.1-mini --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser qwen3`, or the same parsers in SGLang, so tool calls and reasoning come back parsed
2. For llama.cpp, `llama-server -hf apodex/Apodex-1.1-mini-GGUF:Q4_K_M --jinja --reasoning-format deepseek`, and the card passes the repository's chat_template.jinja with --chat-template-file
3. Pass tools through the API's tools parameter rather than in the system prompt, as the card asks
4. The card recommends temperature 1.0, top_p 0.95, repetition_penalty 1.05 and max_tokens up to 32,768
5. Send your own system prompt, or set identity_mode, since the template otherwise adds an Apodex identity block
6. The template keeps all earlier reasoning in the context unless `preserve_thinking` is false, which grows long agent sessions
7. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention
8. The card's Python example has a broken line where it runs the tool (available_toolsname), so fix it to `available_tools[name](**args)` before running
9. Validate JSON output yourself, since structured output isn't documented

### 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

## Questions

### Which is better for AI agents, Apodex-1.1-mini or Laguna XS 2.1?

Apodex-1.1-mini and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C). Laguna XS 2.1 leads on documentation and upkeep.


## For agents

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

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- [Laguna XS 2.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-397b.md)
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- [Laguna XS 2.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-6-35b-a3b.md)
- [Laguna XS 2.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-27b.md)
- [Laguna XS 2.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-flash-next.md)
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- [Laguna XS 2.1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-next.md)
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- [Laguna XS 2.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-30b-a3b-instruct.md)
- [Laguna XS 2.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-32b-instruct.md)
- [Laguna XS 2.1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-4b-instruct.md)
- [Laguna XS 2.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-8b-instruct.md)
- [Laguna XS 2.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwopus3-8-27b-flash-v2.md)
- [Laguna XS 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-smollm3-3b.md)
- [Laguna XS 2.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-spark-x2-6-4b.md)
- [Laguna XS 2.1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-27b.md)
- [Laguna XS 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next.md)
- [Laguna XS 2.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.md)

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