# Ornith-1.5-397B vs Qwen3.5-2B

> Ornith-1.5-397B scores 59 (C) to Qwen3.5-2B's 50.5 (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-1-5-397b-vs-qwen3-5-2b
- Markdown: https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.md (~6,050 tokens)
- Slim: https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.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-1.5-397B scores 59 (C) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 1 of 4 scored categories. Qwen3.5-2B leads on reach and risk. Both do open-weight models you run yourself.

- Ornith-1.5-397B: grade C, 59/100, rank #64 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/ornith-1-5-397b.md · JSON https://www.anchorterminal.com/api/v1/tools/ornith-1-5-397b.json
- Qwen3.5-2B: grade D, 50.5/100, rank #92 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-2b.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-1.5-397B (C)

Good for: A self-hosted frontier-scale coding agent on an 8-GPU server, where a clear licence file and an answering publisher aren't required

Ahead on:
- Agent interface, 85 against 60

Watch for: Needs about 290 GB of memory at 4 bits and about 970 GB in BF16, so it doesn't fit the reference machine

### Qwen3.5-2B (D)

Good for: Builders who want a cheap local helper or fine-tuning base for narrow tasks and image reading on a laptop, small GPU or CPU

Ahead on:
- Reach, 80 against 65
- Risk, 55 against 50

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.0 out of 5

Watch for: No quantised build from Alibaba, and only one inference provider


## Score by category

| Category | Weight | Ornith-1.5-397B | Qwen3.5-2B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 65 | 80 | Qwen3.5-2B +15 |
| Risk | 20% (20 this run) | 50 | 55 | Qwen3.5-2B +5 |
| Agent interface | 10% (10 this run) | 85 | 60 | Ornith-1.5-397B +25 |
| Documentation and upkeep | 10% (10 this run) | 36 | 37 | Qwen3.5-2B +1 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **59 · C** | **50.5 · D** | |

## Facts side by side

| Fact | Ornith-1.5-397B | Qwen3.5-2B |
| --- | --- | --- |
| 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 | 2/5 (4) | 3/5 (4) |

## Verdicts

**Ornith-1.5-397B.** Ornith's flagship coding and terminal-agent cousin, with XML tool calls that vLLM and SGLang parse and 262,144 tokens of context. It needs about 290 GB even at 4 bits, so a multi-GPU server, not the 128 GB reference machine. The main risk is an absent publisher, with no licence file, no safety results and files replaced without a note.

**Qwen3.5-2B.** A small vision-language cousin for prototypes, fine-tuning and light local steps such as tool calls, tagging or reading an image, running in about 2 GB at 4 bits 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 safety results or answers from Alibaba since March.

## Before you call either

### Ornith-1.5-397B

1. Start it with the card's vLLM command at `--tensor-parallel-size 8`, or `ollama run ornith-1.5:397b` on a machine with about 300 GB of memory
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. When downloading the NVFP4 build, fetch only the files its model.safetensors.index.json names (the 25-shard set, 241.7 GB), not the eight extra shards
6. Pin a revision when you download, since Ornith has replaced files in place
7. Validate JSON output yourself, since structured output isn't documented

### Qwen3.5-2B

1. Smallest start is `ollama run qwen3.5:2b-q4_K_M` (1.9 GB); plain `qwen3.5:2b` pulls the 2.7 GB Q8_0 build
2. Full precision `vllm serve Qwen/Qwen3.5-2B --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-1.5-397B or Qwen3.5-2B?

Ornith-1.5-397B scores 59 (C) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 1 of 4 scored categories. Qwen3.5-2B leads on reach and risk.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "ornith-1-5-397b", "b": "qwen3-5-2b"}`. From a terminal: `anchor compare ornith-1-5-397b qwen3-5-2b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ornith-1-5-397b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-2b.json

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

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