# Apodex-1.1-mini vs Qwen3-VL-2B-Instruct

> Apodex-1.1-mini and Qwen3-VL-2B-Instruct 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-qwen3-vl-2b-instruct
- Markdown: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-2b-instruct.md (~6,450 tokens)
- Slim: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-2b-instruct.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-2b-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

Apodex-1.1-mini and Qwen3-VL-2B-Instruct score within a point of each other on agent readiness, 61 (C) and 61 (C). Qwen3-VL-2B-Instruct leads on reach. 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
- Qwen3-VL-2B-Instruct: grade C, 61/100, rank #45 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-vl-2b-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

### 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
- Agent interface, 85 against 60
- Documentation and upkeep, 38 against 31

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

### Qwen3-VL-2B-Instruct (C)

Good for: An agent on a laptop or small edge device that needs a local model to read images, documents and video in about 2 GB

Ahead on:
- Reach, 95 against 85

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


## Score by category

| Category | Weight | Apodex-1.1-mini | Qwen3-VL-2B-Instruct | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 85 | 95 | Qwen3-VL-2B-Instruct +10 |
| Risk | 20% (20 this run) | 65 | 55 | Apodex-1.1-mini +10 |
| Agent interface | 10% (10 this run) | 85 | 60 | Apodex-1.1-mini +25 |
| Documentation and upkeep | 10% (10 this run) | 38 | 31 | Apodex-1.1-mini +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Apodex-1.1-mini | Qwen3-VL-2B-Instruct |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Apodex AI | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-25 | 2025-11-01 |
| 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 | 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.

**Qwen3-VL-2B-Instruct.** The smallest Qwen3-VL cousin, for reading screenshots, documents, charts and video on a laptop or edge box, running in about 2 GB from Alibaba's Q4_K_M GGUF in every major runtime under plain Apache 2.0. Qwen hasn't answered repository questions or published safety work, so keep a human or a check in the loop before it drives a GUI.

## 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

### Qwen3-VL-2B-Instruct

1. Start it with `llama-server -hf Qwen/Qwen3-VL-2B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:2b-instruct`
2. In Ollama the plain `qwen3-vl:2b` tag is the Thinking edition, so name `2b-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, Apodex-1.1-mini or Qwen3-VL-2B-Instruct?

Apodex-1.1-mini and Qwen3-VL-2B-Instruct score within a point of each other on agent readiness, 61 (C) and 61 (C). Qwen3-VL-2B-Instruct leads on reach.


## For agents

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

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- [MiniCPM-o 4.5 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-2b-instruct.md)
- [MiniCPM5-2B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-2b-instruct.md)
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- [MiniMax-M2.7 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-2b-instruct.md)
- [Muse Glimmer 30B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-vl-2b-instruct.md)
- [Nemotron 3.5 Lightning 30B A3B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-vl-2b-instruct.md)
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- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-2b-instruct.md)
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- [Nemotron 3 Ultra 550B A55B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-2b-instruct.md)
- [occamy-1.0 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct.md)
- [Ornith-1.5-35B-A3B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-vl-2b-instruct.md)
- [Ornith-1.5-397B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-vl-2b-instruct.md)
- [Ornith-1.5-9B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-vl-2b-instruct.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-vl-2b-instruct.md)
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- [Qwen3-VL-2B-Instruct vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-swift-1-5-qwen3-8-27b.md)
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