# Arete-27B vs Qwen3.5-4B

> Qwen3.5-4B scores 61.2 (C) to Arete-27B's 55.1 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-4b
- Markdown: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-4b.md (~8,300 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: 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)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

Qwen3.5-4B scores 61.2 (C) on agent readiness against Arete-27B's 55.1 (C), and leads in 2 of 4 scored categories. Arete-27B leads on documentation and upkeep. Both do open-weight models you run yourself.

- Arete-27B: grade C, 55.1/100, rank #123 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/arete-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/arete-27b.json
- Qwen3.5-4B: grade C, 61.2/100, rank #38 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-4b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Arete-27B (C)

Good for: Agents that want Qwen3.8-27B's coding and tool use without its handling of politically sensitive topics, on a 24 GB card or a 128 GB machine

Ahead on:
- Documentation and upkeep, 63 against 34

Watch for: No quantised build from Nous Research, so the GGUF route depends on a third party

### Qwen3.5-4B (C)

Good for: Agents that want a cheap local helper for tool calls, short reasoning and reading images on a laptop or small GPU

Ahead on:
- Reach, 85 against 50
- Agent interface, 70 against 60

Watch for: No quantised build from Alibaba for this size


## Why the edge

### Reach: Qwen3.5-4B +35

- Arete-27B (50): Memory 10, the only build from Nous Research is the 54.7 GB BF16 release, which needs about 66 GB and fits the reference machine. Runtimes 15, vLLM, SGLang and Transformers run the base's architecture from those files, and llama.cpp isn't credited because Nous Research publishes no GGUF. Builds 0, no quantised build of its own. Terms 15, Apache 2.0. Download 10, not gated. Hosted 0, no provider. 10 + 15 + 0 + 15 + 10 + 0 = 50.
- Qwen3.5-4B (85): Memory earns the full 30 because Ollama's own Q4_K_M build is 3.3 GB, about 4 GB with the fifth added, though Alibaba itself publishes no quantised 4B, so builds scores 0. Runtimes reach the 25 cap on vLLM's stable release, Transformers 5.2.0, llama.cpp, Ollama's library and LM Studio's catalogue. Apache 2.0 with nothing added gives the full 15 for terms, the ungated repository the full 10 for download, and two providers (featherless-ai, live on Hugging Face on 2 November, and Doubleword's own list per the 21 October check) the 5 for hosted too. 30 + 25 + 0 + 15 + 10 + 5 = 85.

### Documentation and upkeep: Arete-27B +29

- Arete-27B (63): Model card 8, no limitations, context length, languages or cut-off. Training data 20, the training pairs and the evaluation set are published with their counts. Last change 20, a commit on 6 November 2026. Responsiveness 0, none of 13 discussions has a reply from Nous Research. Version policy 5, a first release. File health 10, the files agree. 8 + 20 + 20 + 0 + 5 + 10 = 63.
- Qwen3.5-4B (34): The card covers five of the seven items and misses limitations and a cut-off (14). Training data is a general description without a cut-off (5). The files last changed on 2 March 2026, 245 days before 2 November, which is within a year (5). No Qwen member has answered any of the 21 discussions that aren't pull requests, four of them opened since 21 October (0), and the GitHub issues couldn't be counted. Earlier 4B models stay in their own repositories without dated notes (5), and two pull requests fixing the template and adding generation_config.json wait unanswered (5). 14 + 5 + 5 + 0 + 5 + 5 = 34.

### Agent interface: Qwen3.5-4B +10

- Arete-27B (60): Chat template 20, a Jinja file in the repository. Tool-calling format 10, only the template says it. Trained tool calling 20, several calls a turn and agentic work as an intended use. Structured output 0 and reasoning control 0, neither is documented on the card. Context 10, 262,144 tokens native. 20 + 10 + 20 + 0 + 0 + 10 = 60.
- Qwen3.5-4B (70): The template ships in the repository (20) and the model was trained for tool use with several calls per turn in the template (20). Tool-calling format gets 10, because the card names the qwen3_coder parser but leaves the declaration and call format to the template. Thinking turns off per request and comes back in think tags split by the qwen3 parser (10), and 262,144 tokens is native (10). Structured output scores 0, as nothing documents JSON output for the model.

## Score by category

| Category | Weight | Arete-27B | Qwen3.5-4B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 50 | 85 | Qwen3.5-4B +35 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 60 | 70 | Qwen3.5-4B +10 |
| Documentation and upkeep | 10% (10 this run) | 63 | 34 | Arete-27B +29 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **55.1 · C** | **61.2 · C** | |

## Facts side by side

| Fact | Arete-27B | Qwen3.5-4B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Nous Research | 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 | 2026-11-06 | 2026-03-02 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 3/5 (4) |

## Verdicts

**Arete-27B.** Qwen3.8-27B with its answers on politically sensitive topics retrained, four days old when read. The training data is published, which is rare. Nous Research ships BF16 only, so a small machine runs it from bartowski's GGUF, and the card documents none of the tool or thinking controls it inherits.

**Qwen3.5-4B.** A small vision-language cousin for tool calls, light agent steps and image or video reading on almost any machine, with switchable thinking. Ollama's 3.3 GB build or the 9.3 GB BF16 files run in every major runtime under plain Apache 2.0. The main risks are no safety results, no structured-output guarantee and no answers from Alibaba since March.

## Before you call either

### Arete-27B

1. Start it with `llama-server -hf bartowski/NousResearch_Arete-27B-GGUF:Q4_K_M --jinja`, a third party's conversion, or serve the BF16 files with vLLM
2. Use the base's parsers in vLLM, `--reasoning-parser qwen3 --tool-call-parser qwen3_coder`, and check tool calls first, since the template differs slightly from Qwen3.8-27B's
3. Thinking switches with `enable_thinking` in the template. The card's own evaluation ran with it off
4. Expect answers on politically sensitive topics to differ from Qwen3.8-27B's. That is what the fine-tune is for
5. Validate JSON output yourself, since structured output isn't documented

### Qwen3.5-4B

1. Smallest start is `ollama run qwen3.5:4b` (Q4_K_M, about 4 GB with context)
2. Full precision `vllm serve Qwen/Qwen3.5-4B --port 8000 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Turn thinking off with `"chat_template_kwargs": {"enable_thinking": false}` in the request body, since it's on by default and `/think` and `/nothink` aren't supported
4. There's no generation_config.json, so pass the card's sampling yourself, for example `temperature=0.7, top_p=0.8, top_k=20, presence_penalty=1.5` without thinking
5. Keep the context at 128K or more if you rely on thinking, and turn on YaRN only past 262,144 tokens
6. Validate any JSON it returns, since structured output isn't documented

## Questions

### Which is better for AI agents, Arete-27B or Qwen3.5-4B?

Qwen3.5-4B scores 61.2 (C) on agent readiness against Arete-27B's 55.1 (C), and leads in 2 of 4 scored categories. Arete-27B leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-4b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-4b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "arete-27b", "b": "qwen3-5-4b"}`. From a terminal: `anchor compare arete-27b qwen3-5-4b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/arete-27b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-4b.json

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- [Arete-27B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-vl-8b-instruct.md)
- [Arete-27B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/arete-27b-vs-qwopus3-8-27b-flash-v2.md)
- [Arete-27B vs Recursive Flint](https://www.anchorterminal.com/compare/arete-27b-vs-recursive-flint.md)
- [Arete-27B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/arete-27b-vs-ripple-65b-preview.md)
- [Arete-27B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/arete-27b-vs-sensenova-loop-9b-preview.md)
- [Arete-27B vs SmolLM3-3B](https://www.anchorterminal.com/compare/arete-27b-vs-smollm3-3b.md)
- [Arete-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/arete-27b-vs-spark-x2-6-4b.md)
- [Arete-27B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/arete-27b-vs-step-3-7-flash.md)
- [Arete-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/arete-27b-vs-swift-1-5-qwen3-8-27b.md)
- [Arete-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/arete-27b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Arete-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/arete-27b-vs-thinkingcap-qwen3-8-27b.md)
- [Arete-27B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/arete-27b-vs-unlimited-ocr-2.md)
- [Arete-27B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/arete-27b-vs-wevisone-vl-2b.md)
- [Arete-27B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/arete-27b-vs-wevisone-vl-4b.md)
- [Arete-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/arete-27b-vs-zaya1-8b.md)
- [BigBang-v1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-4b.md)
- [Carbon-X vs Qwen3.5-4B](https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-4b.md)
- [Cola2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-4b.md)
- [Cosmos-Reason2-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-4b.md)
- [Darwin-36B-Opus vs Qwen3.5-4B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.md)
- [DeepSeek-V3.2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-4b.md)
- [DeepSeek V4.1 Flash vs Qwen3.5-4B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-5-4b.md)
- [DeepSeek-V4-Flash-0731 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-5-4b.md)
- [Devstral Small 2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-4b.md)
- [DiffusionGemma 26B A4B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-5-4b.md)
- [EXAONE 4.5 33B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-4b.md)
- [Gemma 4 12B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-4b.md)
- [Gemma 4 26B A4B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-5-4b.md)
- [Gemma 4 31B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-5-4b.md)
- [Gemma 4 E2B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-5-4b.md)
- [Gemma 4 E4B IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-5-4b.md)
- [GLM-4.5-Air vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-5-4b.md)
- [GLM-4.7-Flash vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-5-4b.md)
- [GLM-5.3-Flash vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-4b.md)
- [GLM-5.3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b.md)
- [gpt-oss-120b vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-4b.md)
- [gpt-oss-20b vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-4b.md)
- [Granite 4.2 30B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-4b.md)
- [Granite 4.2 3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-5-4b.md)
- [Granite 4.2 8B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-4b.md)
- [Hy-Memory-30B-A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen3-5-4b.md)
- [Hy3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b.md)
- [Inkling-Small vs Qwen3.5-4B](https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b.md)
- [Inkling vs Qwen3.5-4B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b.md)
- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3.5-4B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-5-4b.md)
- [Kimi K3.1 Pro vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen3-5-4b.md)
- [Kimi K3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b.md)
- [Kolibri-1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-4b.md)
- [Kronos vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-4b.md)
- [Laguna M.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b.md)
- [Laguna S 2.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-4b.md)
- [Laguna XS 2.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-4b.md)
- [LBS-27B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-4b.md)
- [LFM2.5-2.6B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-5-4b.md)
- [LFM3-1.7B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-4b.md)
- [LFM3-Audio-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-4b.md)
- [LFM3-Omni-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen3-5-4b.md)
- [LFM3-VL-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen3-5-4b.md)
- [Ling-3.0-tiny vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-4b.md)
- [Ling-3.1-flash-1019 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-4b.md)
- [LongCat-2.5 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-4b.md)
- [MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-4b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-4b.md)
- [MiniCPM-o 4.5 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-4b.md)
- [MiniCPM-V 4.7 1B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-qwen3-5-4b.md)
- [MiniCPM-V 4.7 35B-A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-qwen3-5-4b.md)
- [MiniCPM5-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-4b.md)
- [MiniMax-M2.5 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-4b.md)
- [MiniMax-M2.7 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-4b.md)
- [MiniMax-M3.1-Flash vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-4b.md)
- [Mistral Large 4 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-4b.md)
- [Muse Glimmer 30B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-5-4b.md)
- [Nanbeige4.2-3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-4b.md)
- [Nanbeige4.3-33B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-5-4b.md)
- [NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-qwen3-5-4b.md)
- [Nemotron 3.5 Lightning 30B A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-5-4b.md)
- [Nemotron 3 Nano 30B A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-4b.md)
- [Nemotron 3 Nano 4B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-5-4b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-5-4b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-4b.md)
- [Nemotron 3 Ultra 550B A55B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-4b.md)
- [North Mini Code 1.0 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-5-4b.md)
- [occamy-1.0 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b.md)
- [Olmo 3 7B Think vs Qwen3.5-4B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b.md)
- [Ornith-1.5-122B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-4b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-4b.md)
- [Ornith-1.5-397B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-4b.md)
- [Ornith-1.5-9B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-4b.md)
- [OTel-2.0-LLM-31B-IT vs Qwen3.5-4B](https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-qwen3-5-4b.md)
- [Qwen-AgentWorld-35B-A3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-4b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-4b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-4b.md)
- [Qwen3.5-0.8B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-4b.md)
- [Qwen3.5-122B-A10B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-4b.md)
- [Qwen3.5-2B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-5-4b.md)
- [Qwen3.5-397B-A17B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-5-4b.md)
- [Qwen3.5-4B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-5-9b.md)
- [Qwen3.5-4B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-27b.md)
- [Qwen3.5-4B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-35b-a3b.md)
- [Qwen3.5-4B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-27b.md)
- [Qwen3.5-4B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-flash-next.md)
- [Qwen3.5-4B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-coder-30b-a3b-instruct.md)
- [Qwen3.5-4B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-coder-next.md)
- [Qwen3.5-4B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-omni-30b-a3b-instruct.md)
- [Qwen3.5-4B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-2b-instruct.md)
- [Qwen3.5-4B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Qwen3.5-4B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-32b-instruct.md)
- [Qwen3.5-4B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.5-4B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-8b-instruct.md)
- [Qwen3.5-4B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3.5-4B vs Recursive Flint](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-recursive-flint.md)
- [Qwen3.5-4B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-ripple-65b-preview.md)
- [Qwen3.5-4B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-sensenova-loop-9b-preview.md)
- [Qwen3.5-4B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-smollm3-3b.md)
- [Qwen3.5-4B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-spark-x2-6-4b.md)
- [Qwen3.5-4B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-step-3-7-flash.md)
- [Qwen3.5-4B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3.5-4B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.5-4B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.5-4B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-unlimited-ocr-2.md)
- [Qwen3.5-4B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-wevisone-vl-2b.md)
- [Qwen3.5-4B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-wevisone-vl-4b.md)
- [Qwen3.5-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-zaya1-8b.md)

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