# Ornith-1.5-35B-A3B vs Qwen3.5-0.8B

> Ornith-1.5-35B-A3B scores 61 (C) to Qwen3.5-0.8B's 46.7 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b
- Markdown: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.md (~6,250 tokens)
- Slim: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.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

Ornith-1.5-35B-A3B scores 61 (C) on agent readiness against Qwen3.5-0.8B's 46.7 (D), and leads in 2 of 4 scored categories. Qwen3.5-0.8B leads on risk and documentation and upkeep. Both do open-weight models you run yourself.

- Ornith-1.5-35B-A3B: grade C, 61/100, rank #43 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/ornith-1-5-35b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/ornith-1-5-35b-a3b.json
- Qwen3.5-0.8B: grade D, 46.7/100, rank #97 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-0-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-0-8b.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

### Ornith-1.5-35B-A3B (C)

Good for: Local coding and terminal agents on a 24 to 32 GB GPU or a Mac, where a clear licence file and an answering publisher aren't required

Ahead on:
- Reach, 90 against 80
- Agent interface, 85 against 60

Watch for: No LICENSE file though the card links one, and no notice for the Apache 2.0 Qwen3.5 and Gemma 4 work it builds on

### Qwen3.5-0.8B (D)

Good for: Builders who want a near-free local helper or fine-tuning base for narrow tasks on a phone-class device, laptop or CPU

Ahead on:
- Risk, 55 against 50
- Documentation and upkeep, 37 against 31

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

Watch for: No quantised build from Alibaba and no inference provider found


## Score by category

| Category | Weight | Ornith-1.5-35B-A3B | Qwen3.5-0.8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 80 | Ornith-1.5-35B-A3B +10 |
| Risk | 20% (20 this run) | 50 | 55 | Qwen3.5-0.8B +5 |
| Agent interface | 10% (10 this run) | 85 | 60 | Ornith-1.5-35B-A3B +25 |
| Documentation and upkeep | 10% (10 this run) | 31 | 37 | Qwen3.5-0.8B +6 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **46.7 · D** | |

## Facts side by side

| Fact | Ornith-1.5-35B-A3B | Qwen3.5-0.8B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Ornith | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-23 | 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 | 2.3/5 (4) | 2.8/5 (4) |

## Verdicts

**Ornith-1.5-35B-A3B.** A mid-size coding and terminal-agent cousin with about 3B active parameters, XML tool calls that vLLM and SGLang parse and 262,144 tokens of context. It runs in about 24 GB from Ornith's MLX 4-bit build or 32 GB from its GGUF. The main risk is an absent publisher, with no licence file, safety results or replies to 35 reports.

**Qwen3.5-0.8B.** A tiny vision-language cousin for prototypes, fine-tuning and light local steps such as routing, tagging or reading an image, running in under 2 GB in every major runtime under plain Apache 2.0. Keep thinking off, since the card warns it loops. The main risk is neglect, with no hosted option, safety results or answers from Alibaba since March.

## Before you call either

### Ornith-1.5-35B-A3B

1. Start it with `ollama run ornith-1.5:35b`, or `llama-server -hf ornith-ai/Ornith-1.5-35B-A3B-GGUF --port 8000 -c 262144` as the card gives it
2. In vLLM pass `--enable-auto-tool-choice --tool-call-parser qwen3_xml --reasoning-parser qwen3`, and in SGLang `--tool-call-parser qwen3_coder --reasoning-parser qwen3`, so tool calls and reasoning come back parsed
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. Pin which template your runtime loads, since chat_template.jinja keeps earlier reasoning and the tokenizer_config.json template drops it
5. Use temperature 0.6, top_p 0.95, top_k 20 for general tasks and temperature 1.0 to reproduce the card's benchmarks
6. Pin a revision when you download, since Ornith has replaced files in place, and add mmproj-Ornith-1.5-35B-BF16.gguf (0.9 GB) for image input in llama.cpp
7. Validate JSON output yourself, since structured output isn't documented

### Qwen3.5-0.8B

1. Smallest start is `ollama run qwen3.5:0.8b`, or `qwen3.5:0.8b-q8_0` at 1.0 GB
2. Full precision `vllm serve Qwen/Qwen3.5-0.8B --port 8000 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Thinking is off by default; if you turn it on with `"chat_template_kwargs": {"enable_thinking": true}`, stream and cut off runaway output, since the card warns of thinking loops, and add `--reasoning-parser qwen3` in vLLM or SGLang to split the reasoning out
4. There's no generation_config.json, so pass the card's sampling yourself, for example `temperature=1.0, top_p=1.0, top_k=20, presence_penalty=2.0` for text without thinking
5. Use it for narrow steps or as a fine-tuning base, not as the main agent, as the card itself suggests
6. Validate any JSON it returns, since structured output isn't documented

## Questions

### Which is better for AI agents, Ornith-1.5-35B-A3B or Qwen3.5-0.8B?

Ornith-1.5-35B-A3B scores 61 (C) on agent readiness against Qwen3.5-0.8B's 46.7 (D), and leads in 2 of 4 scored categories. Qwen3.5-0.8B leads on risk and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "ornith-1-5-35b-a3b", "b": "qwen3-5-0-8b"}`. From a terminal: `anchor compare ornith-1-5-35b-a3b qwen3-5-0-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ornith-1-5-35b-a3b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-0-8b.json

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- [Ornith-1.5-35B-A3B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-122b-a10b.md)
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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-1.5-35B-A3B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-9b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-6-27b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-6-35b-a3b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-8-27b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-8-flash-next.md)
- [Ornith-1.5-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-coder-30b-a3b-instruct.md)
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- [Ornith-1.5-35B-A3B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-vl-32b-instruct.md)
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- [Ornith-1.5-35B-A3B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwopus3-8-27b-flash-v2.md)
- [Ornith-1.5-35B-A3B vs SmolLM3-3B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-smollm3-3b.md)
- [Ornith-1.5-35B-A3B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-spark-x2-6-4b.md)
- [Ornith-1.5-35B-A3B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-swift-1-5-qwen3-8-27b.md)
- [Ornith-1.5-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Ornith-1.5-35B-A3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-thinkingcap-qwen3-8-27b.md)
- [Ornith-1.5-397B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-0-8b.md)
- [Ornith-1.5-9B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-0-8b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-0-8b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b.md)
- [Qwen3.5-0.8B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-122b-a10b.md)
- [Qwen3.5-0.8B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-2b.md)
- [Qwen3.5-0.8B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-397b-a17b.md)
- [Qwen3.5-0.8B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-4b.md)
- [Qwen3.5-0.8B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-9b.md)
- [Qwen3.5-0.8B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-27b.md)
- [Qwen3.5-0.8B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-35b-a3b.md)
- [Qwen3.5-0.8B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-8-27b.md)
- [Qwen3.5-0.8B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-8-flash-next.md)
- [Qwen3.5-0.8B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-coder-30b-a3b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-coder-next.md)
- [Qwen3.5-0.8B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-omni-30b-a3b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-2b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-32b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-8b-instruct.md)
- [Qwen3.5-0.8B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3.5-0.8B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-smollm3-3b.md)
- [Qwen3.5-0.8B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-spark-x2-6-4b.md)
- [Qwen3.5-0.8B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3.5-0.8B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.5-0.8B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-thinkingcap-qwen3-8-27b.md)

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