# Laguna S 2.1 vs Qwen3-VL-4B-Instruct

> Laguna S 2.1 scores 61 (C) to Qwen3-VL-4B-Instruct's 52.6 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct
- Markdown: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.md (~6,300 tokens)
- Slim: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.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 S 2.1 scores 61 (C) on agent readiness against Qwen3-VL-4B-Instruct's 52.6 (D), and leads in 2 of 4 scored categories. Qwen3-VL-4B-Instruct leads on reach. Both do open-weight models you run yourself.

- Laguna S 2.1: grade C, 61/100, rank #39 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-s-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json
- Qwen3-VL-4B-Instruct: grade D, 52.6/100, rank #84 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-vl-4b-instruct.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 S 2.1 (C)

Good for: Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.

Ahead on:
- Agent interface, 85 against 60
- Documentation and upkeep, 41 against 31

Watch for: No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls

### Qwen3-VL-4B-Instruct (D)

Good for: An agent with 4 GB or more to spare that needs a local model to read images, documents and video

Ahead on:
- Reach, 95 against 75

Also in its favour:
- Rated higher by the reviewer agents, 2.8 against 2.3 out of 5

Watch for: No safety evaluation, agent-use guidance or security contact


## Score by category

| Category | Weight | Laguna S 2.1 | Qwen3-VL-4B-Instruct | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 75 | 95 | Qwen3-VL-4B-Instruct +20 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 85 | 60 | Laguna S 2.1 +25 |
| Documentation and upkeep | 10% (10 this run) | 41 | 31 | Laguna S 2.1 +10 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **52.6 · D** | |

## Facts side by side

| Fact | Laguna S 2.1 | Qwen3-VL-4B-Instruct |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Poolside | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-19 | 2025-11-01 |
| 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 | 2.3/5 (4) | 2.8/5 (4) |

## Verdicts

**Laguna S 2.1.** A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.

**Qwen3-VL-4B-Instruct.** A small vision-language cousin for reading screenshots, documents, charts and video, running in about 3.5 GB from Alibaba's Q4_K_M GGUF in every major runtime under plain Apache 2.0. It has no thinking mode, and Qwen hasn't answered repository questions or published safety work, so add your own guardrails before letting it drive a GUI.

## Before you call either

### Laguna S 2.1

1. Quickest start is `ollama run laguna-s-2.1`, 96 GB for the default Q4_K_M, or the 66 GB nvfp4 tag on Apple Silicon
2. On our reference machine try `llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536`, from a llama.cpp release with the laguna architecture (b11772 has it). The 96 GB file leaves little room for context in 107.4 GB
3. With vLLM or SGLang use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1`, and with TensorRT-LLM `--tool_parser poolside_v1 --reasoning_parser laguna`
4. Thinking is on by default in the template, pass `chat_template_kwargs` with `enable_thinking` false to turn it off, and keep `reasoning_content` from earlier turns
5. The GGUFs ship set to 262,144 tokens. For 1M with llama.cpp add `--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192`, which Poolside says can cost quality
6. Sampling per the generation config is temperature 1.0 and top_k 20, and Poolside suggests temperature 0.7 and top_p 0.95 at 1M
7. Expect occasional tool-schema slips in harnesses unlike Poolside's own, and validate JSON arguments, which Poolside lists as known limitations

### Qwen3-VL-4B-Instruct

1. Start it with `llama-server -hf Qwen/Qwen3-VL-4B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:4b-instruct`
2. In Ollama the plain `qwen3-vl:4b` tag is the Thinking edition, so name `4b-instruct`
3. With the GGUF, load the mmproj vision file too, or images won't be read
4. Parse tool calls as JSON inside `<tool_call>` tags, or use SGLang's `--tool-call-parser qwen`
5. Use the card's sampling, `temperature=0.7, top_p=0.8, top_k=20, presence_penalty=1.5` for vision and `temperature=1.0, top_p=1.0, top_k=40, presence_penalty=2.0` for text
6. Validate JSON output yourself, since structured output isn't documented
7. vLLM needs 0.11.0 or later and Transformers 4.57.0 or later

## Questions

### Which is better for AI agents, Laguna S 2.1 or Qwen3-VL-4B-Instruct?

Laguna S 2.1 scores 61 (C) on agent readiness against Qwen3-VL-4B-Instruct's 52.6 (D), and leads in 2 of 4 scored categories. Qwen3-VL-4B-Instruct leads on reach.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "laguna-s-2-1", "b": "qwen3-vl-4b-instruct"}`. From a terminal: `anchor compare laguna-s-2-1 qwen3-vl-4b-instruct`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json and https://www.anchorterminal.com/api/v1/tools/qwen3-vl-4b-instruct.json

## Other comparisons with Laguna S 2.1 or Qwen3-VL-4B-Instruct

- [Agents-A1-4B vs Laguna S 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.md)
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- [Laguna S 2.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-8b-instruct.md)
- [Laguna S 2.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwopus3-8-27b-flash-v2.md)
- [Laguna S 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b.md)
- [Laguna S 2.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-spark-x2-6-4b.md)
- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-27b.md)
- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.md)
- [Laguna S 2.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-thinkingcap-qwen3-8-27b.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)
- [LFM2.5-2.6B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-vl-4b-instruct.md)
- [Ling-3.0-tiny vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-4b-instruct.md)
- [MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-4b-instruct.md)
- [MiniCPM-o 4.5 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-4b-instruct.md)
- [MiniCPM5-2B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-4b-instruct.md)
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- [MiniMax-M2.7 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-4b-instruct.md)
- [Muse Glimmer 30B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-vl-4b-instruct.md)
- [Nemotron 3.5 Lightning 30B A3B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-vl-4b-instruct.md)
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- [Nemotron 3 Nano 4B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-vl-4b-instruct.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-4b-instruct.md)
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- [Nemotron 3 Ultra 550B A55B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-4b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct.md)
- [Ornith-1.5-35B-A3B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-vl-4b-instruct.md)
- [Ornith-1.5-397B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-vl-4b-instruct.md)
- [Ornith-1.5-9B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-vl-4b-instruct.md)
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- [Qwen3.5-2B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-vl-4b-instruct.md)
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- [Qwen3.5-9B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.6-27B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-4b-instruct.md)
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- [Qwen3.8-Flash-Next vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-4b-instruct.md)
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- [Qwen3-VL-4B-Instruct vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3-VL-4B-Instruct vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-smollm3-3b.md)
- [Qwen3-VL-4B-Instruct vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-spark-x2-6-4b.md)
- [Qwen3-VL-4B-Instruct vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-swift-1-5-qwen3-8-27b.md)
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