# Cosmos-Reason2-2B vs Qwen3.5-9B

> Qwen3.5-9B scores 60.5 (C) to Cosmos-Reason2-2B's 59.5 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b
- Markdown: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.md (~6,150 tokens)
- Slim: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.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

Qwen3.5-9B scores 60.5 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 2 of 4 scored categories. Cosmos-Reason2-2B leads on risk and documentation and upkeep. Both do open-weight models you run yourself.

- Cosmos-Reason2-2B: grade C, 59.5/100, rank #59 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/cosmos-reason2-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json
- Qwen3.5-9B: grade C, 60.5/100, rank #53 of 100 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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Cosmos-Reason2-2B (C)

Good for: Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces

Ahead on:
- Risk, 60 against 55
- Documentation and upkeep, 39 against 34

Watch for: Gated behind a click-through licence that needs a Hugging Face account

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

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

Ahead on:
- Reach, 85 against 65
- Agent interface, 70 against 65

Watch for: No quantised build from Qwen itself


## Score by category

| Category | Weight | Cosmos-Reason2-2B | Qwen3.5-9B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 65 | 85 | Qwen3.5-9B +20 |
| Risk | 20% (20 this run) | 60 | 55 | Cosmos-Reason2-2B +5 |
| Agent interface | 10% (10 this run) | 65 | 70 | Qwen3.5-9B +5 |
| Documentation and upkeep | 10% (10 this run) | 39 | 34 | Cosmos-Reason2-2B +5 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **59.5 · C** | **60.5 · C** | |

## Facts side by side

| Fact | Cosmos-Reason2-2B | Qwen3.5-9B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-03-10 | 2026-03-02 |
| Terms last updated |  | 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) | 2.5/5 (4) |

## Verdicts

**Cosmos-Reason2-2B.** A small local cousin for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.

**Qwen3.5-9B.** A small dense vision-language cousin with trained tool calling, switchable thinking and a 262,144-token context, for local agent subtasks. Ollama's 4-bit build needs about 8 GB and the BF16 files about 24 GB, in every major runtime. The main risk is neglect, with no file changes since March, no replies from Qwen to reports and no safety results.

## Before you call either

### Cosmos-Reason2-2B

1. Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading
2. Serve it with `vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{"video": {"num_frames": -1}}' --reasoning-parser qwen3`, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises
3. For local video or images, make a folder for them (`mkdir -p media`) and pass `--allowed-local-media-path "$(pwd)/media"`, so the server can read only that folder, not everything under the directory you start it from
4. Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off
5. For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply
6. Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself
7. Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks

### 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, Cosmos-Reason2-2B or Qwen3.5-9B?

Qwen3.5-9B scores 60.5 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 2 of 4 scored categories. Cosmos-Reason2-2B leads on risk and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cosmos-reason2-2b", "b": "qwen3-5-9b"}`. From a terminal: `anchor compare cosmos-reason2-2b qwen3-5-9b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-9b.json

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