# Darwin-36B-Opus vs Qwen3.5-4B

> Qwen3.5-4B and Darwin-36B-Opus score within a point of each other for open-weight models you run yourself, 61.2 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b
- Markdown: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.md (~6,000 tokens)
- Slim: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.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

Qwen3.5-4B and Darwin-36B-Opus score within a point of each other on agent readiness, 61.2 (C) and 61 (C). Darwin-36B-Opus leads on documentation and upkeep. Both do open-weight models you run yourself.

- Darwin-36B-Opus: grade C, 61/100, rank #37 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/darwin-36b-opus.md · JSON https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json
- Qwen3.5-4B: grade C, 61.2/100, rank #33 of 100 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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Darwin-36B-Opus (C)

Good for: Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required

Ahead on:
- Documentation and upkeep, 51 against 34

Watch for: The merge method is proprietary and the current weights include an undescribed targeted refinement

### 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 80

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.5 out of 5

Watch for: No quantised build from Alibaba for this size


## Score by category

| Category | Weight | Darwin-36B-Opus | Qwen3.5-4B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 80 | 85 | Qwen3.5-4B +5 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 70 | 70 | even |
| Documentation and upkeep | 10% (10 this run) | 51 | 34 | Darwin-36B-Opus +17 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61.2 · C** | |

## Facts side by side

| Fact | Darwin-36B-Opus | Qwen3.5-4B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | FINAL-Bench (VIDRAFT) | 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 | 2026-04-23 | 2026-03-02 |
| 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 | 2.5/5 (4) | 3/5 (4) |

## Verdicts

**Darwin-36B-Opus.** A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.

**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

### Darwin-36B-Opus

1. Quickest start is `llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja`, about 21 GB of files
2. On the reference machine BF16 fits, `vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parsers for Qwen3.6's format
3. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention
4. The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces
5. generation_config.json stops only on the end-of-text token, so add `<|im_end|>` as a stop token if a runtime keeps generating after the turn ends
6. Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files
7. 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, Darwin-36B-Opus or Qwen3.5-4B?

Qwen3.5-4B and Darwin-36B-Opus score within a point of each other on agent readiness, 61.2 (C) and 61 (C). Darwin-36B-Opus leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "darwin-36b-opus", "b": "qwen3-5-4b"}`. From a terminal: `anchor compare darwin-36b-opus qwen3-5-4b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-4b.json

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- [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)
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- [Qwen3.5-4B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-35b-a3b.md)
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- [Qwen3.5-4B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-flash-next.md)
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- [Qwen3.5-4B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-30b-a3b-instruct.md)
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- [Qwen3.5-4B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-8b-instruct.md)
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- [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 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)

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