# Cosmos-Reason2-2B vs Qwen3.8-Flash-Next

> Qwen3.8-Flash-Next scores 61.8 (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-qwen3-8-flash-next
- Markdown: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.md (~6,700 tokens)
- Slim: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.min.md (~580 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.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

Qwen3.8-Flash-Next scores 61.8 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 1 of 4 scored categories. Cosmos-Reason2-2B leads on risk. 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
- Qwen3.8-Flash-Next: grade C, 61.8/100, rank #31 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-8-flash-next.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.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 45

Also in its favour:
- Rated higher by the reviewer agents, 2.5 against 2.0 out of 5

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

### Qwen3.8-Flash-Next (C)

Good for: Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business.

Ahead on:
- Agent interface, 70 against 65

Watch for: No build fits the reference machine's 107.4 GB, and Ollama's smallest Linux build is 120 GB


## Score by category

| Category | Weight | Cosmos-Reason2-2B | Qwen3.8-Flash-Next | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 65 | 65 | even |
| Risk | 20% (20 this run) | 60 | 45 | Cosmos-Reason2-2B +15 |
| Agent interface | 10% (10 this run) | 65 | 70 | Qwen3.8-Flash-Next +5 |
| Documentation and upkeep | 10% (10 this run) | 39 | 36 | Cosmos-Reason2-2B +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **59.5 · C** | **61.8 · C** | |

## Facts side by side

| Fact | Cosmos-Reason2-2B | Qwen3.8-Flash-Next |
| --- | --- | --- |
| 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 | Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-03-10 | 2026-08-31 |
| 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 (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.

**Qwen3.8-Flash-Next.** A large sparse cousin with 6B active parameters for agentic coding and multimodal work, previewing Qwen's next architecture. It needs a 128 GB Mac for Ollama's MLX build or about 144 GB for the 4-bit GGUF, and Qwen Cloud serves it. The main risk is a licence that needs a separate deal for hosted-model and coding or office assistant businesses.

## 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

### Qwen3.8-Flash-Next

1. On a 128 GB Mac start it with `ollama run qwen3.8-flash-next:125b-mlx` (105 GB, NVFP4), on Linux the smallest Ollama build is `qwen3.8-flash-next:125b-a6b-q4_K_M` at 120 GB, which won't fit a 107.4 GB GPU share
2. On a server, `vllm serve Qwen/Qwen3.8-Flash-Next-FP8 --tensor-parallel-size 4 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Use the qwen3_coder tool parser and the qwen3 reasoning parser, as Qwen's GitHub README does
4. Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false to skip it, and read the reasoning from `reasoning_content`, even though SGLang's cookbook says thinking can't be turned off
5. `reasoning_effort` takes xhigh (default), medium or low, and any other value makes the template raise an error
6. Send at most one system message and put it first, since the template raises an error otherwise
7. Sampling per the card is temperature 1.0 and top_p 0.95 when thinking, temperature 0.7, top_p 0.8 and presence_penalty 1.5 without
8. vLLM keeps the 51B n-gram table in host memory on 80 GB GPUs by default, per its recipe
9. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
10. Read the Qwen Community License before serving it to others as an API or inside a coding or office assistant product

## Questions

### Which is better for AI agents, Cosmos-Reason2-2B or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next scores 61.8 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 1 of 4 scored categories. Cosmos-Reason2-2B leads on risk.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cosmos-reason2-2b", "b": "qwen3-8-flash-next"}`. From a terminal: `anchor compare cosmos-reason2-2b qwen3-8-flash-next`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.json

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