# Arete-27B vs Qwen3.5-9B

> Qwen3.5-9B scores 60.5 (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-qwen3-5-9b
- Markdown: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-9b.md (~8,500 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

Qwen3.5-9B scores 60.5 (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
- Qwen3.5-9B: grade C, 60.5/100, rank #87 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-9b.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

### Qwen3.5-9B (C)

Good for: Agents that want a small multimodal tool-calling model on a laptop or a 16 GB GPU, under a plain licence

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

Watch for: No quantised build from Qwen itself


## Why the edge

### Reach: Qwen3.5-9B +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.
- Qwen3.5-9B (85): Memory 30, Qwen publishes no quantised 9B, so the smallest 4-bit build from a runtime's own library is Ollama's qwen3.5:9b at 6.6 GB, about 7.9 GB with the fifth added, well under 16 GB. Runtimes 25, the cap, with vLLM listed in its stable docs, Transformers at released tags, llama.cpp, Ollama's library, LM Studio's own catalogue and SGLang all running the architecture. Builds 0, Qwen's FP8 and GPTQ repositories cover only the 27B and larger Qwen3.5 models, so every quantisation of the 9B is someone else's. Terms 15, plain Apache 2.0. Download 10, the repository isn't gated. Hosted 5, Together, Featherless AI, OVHcloud and DeepInfra are live for it on its Hugging Face page. 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.
- Qwen3.5-9B (34): Model card 14, it covers intended use, architecture, parameters, context and 201 languages but gives no limitations and no knowledge cut-off. Training data 5, a general line about trillions of multimodal tokens with no cut-off. Last change 5, the files and card last changed on 2 March 2026 (c202236), 247 days before 4 November, within a year. Responsiveness 0, no Qwen member replied in any of the 40 most recent of the 45 discussions that aren't pull requests (2 March to 29 September 2026). Version policy 5, a first release that was never replaced in place, with no dated notes across generations. File health 5, two reports about the files and card (15 and 51) are still open with no reply. 14 + 5 + 5 + 0 + 5 + 5 = 34. The card's highlights mention sparse Mixture-of-Experts for the series while this 9B is dense, but its own overview matches config.json, so it's not counted as a contradiction.

### Agent interface: Qwen3.5-9B +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.
- Qwen3.5-9B (70): Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card names the qwen3_coder parser for vLLM and SGLang but leaves the declaration and return format to the template, and Qwen's own function-calling guide still describes Qwen3's Hermes format. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, nothing documents asking the weights for JSON. Reasoning control 10, thinking turns off per request with enable_thinking false and the reasoning comes back in think tags that the qwen3 parser splits out. Context 10, 262,144 tokens native.

## Score by category

| Category | Weight | Arete-27B | Qwen3.5-9B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 50 | 85 | Qwen3.5-9B +35 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 60 | 70 | Qwen3.5-9B +10 |
| Documentation and upkeep | 10% (10 this run) | 63 | 34 | Arete-27B +29 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **55.1 · C** | **60.5 · C** | |

## Facts side by side

| Fact | Arete-27B | Qwen3.5-9B |
| --- | --- | --- |
| 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 | 2.5/5 (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.

**Qwen3.5-9B.** A small dense vision-language model with trained tool calling, thinking that turns off per request and a 262,144-token context. Ollama's 4-bit build is 6.6 GB and the BF16 files 19.3 GB, and every major runtime loads it. The files haven't changed since 2 March 2026, Qwen answered none of the 40 latest discussions, and no safety results are published.

## 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

### Qwen3.5-9B

1. Smallest start is `ollama run qwen3.5:9b` (6.6 GB, q4_k_m)
2. On vLLM run `vllm serve Qwen/Qwen3.5-9B --port 8000 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, or tool calls come back as text
3. Tool calls use the XML style `<tool_call><function=name><parameter=x>`, not Hermes JSON, so use the qwen3_coder parser and not hermes
4. Thinking is on by default; pass `chat_template_kwargs` with `enable_thinking` false for short tasks, since `/nothink` isn't supported
5. There's no generation_config.json, so pass sampling yourself, temperature 1.0, top_p 0.95, top_k 20, presence_penalty 1.5 when thinking, or 0.7, 0.8, 20, 1.5 without
6. Keep at least 128K of context when thinking, and turn on YaRN only beyond 262,144 tokens
7. Validate JSON output yourself or use the runtime's guided decoding

## Questions

### Which is better for AI agents, Arete-27B or Qwen3.5-9B?

Qwen3.5-9B scores 60.5 (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-qwen3-5-9b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-9b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "arete-27b", "b": "qwen3-5-9b"}`. From a terminal: `anchor compare arete-27b qwen3-5-9b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/arete-27b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-9b.json

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

---

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