Head to head · Open-weight models you run yourself · October 2026 research run
Cosmos-Reason2-2B vs Hy-Memory-30B-A3B
Hy-Memory-30B-A3B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 2 of 4 scored categories. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons
Which one, for what
Best for Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
Gated behind a click-through licence that needs a Hugging Face account
Best for Agents with an external memory framework that want a local model for the write path on a 24 GB card
Ahead on
- Reach, 85 against 65
- Documentation and upkeep, 68 against 39
Watch for
Not a general assistant or a tool caller
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Documentation and upkeep Hy-Memory-30B-A3B +29
Cosmos-Reason2-2B 39
The card misses languages and a cut-off (14). Training data is named by dataset without sizes or a cut-off (5). The Hub repository last changed on 30 April 2026, 188 days before this check, which alone gives 5. NVIDIA's GitHub repository last changed with a README redirect to Cosmos 3 on 7 June 2026, 150 days back, and this run counts the publisher's documentation commits on this line (10). None of its 3 discussions has an NVIDIA reply, counted by author flags on 4 November (0). The 2B's weights were replaced in place in March with a dated line, and the family is now superseded by Cosmos 3 with a dated note (5). The gated files couldn't be checked against the card, which itself mixes float16 and BF16 and links a newer licence than the gate shows (5). 14 + 5 + 10 + 0 + 5 + 5 = 39.
Hy-Memory-30B-A3B 68
Model card 8, Intended use (the write path of Mem0, MemOS and Hy-Memory), parameters (30B, about 3B active) and languages (English and Chinese, in the metadata) are there. Training data 5, A general description of the two training stages inside the harnesses, with no datasets, sizes or cut-off. Last change 20, the last commit, on 16 October 2026, added the licence and the card, 25 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (16 to 30 October 2026), 3 have a reply from a tencent organisation member. Version policy 5, A first release, with nothing replaced. File health 10, Config, tokenizer and template agree on the architecture, the context and the thinking levels. 8 + 5 + 20 + 20 + 5 + 10 = 68.
Reach Hy-Memory-30B-A3B +20
Cosmos-Reason2-2B 65
Memory earns the full 30 because the BF16 file is 4.9 GB, about 5.9 GB with the fifth added, though NVIDIA itself asks for 24 GB of GPU memory. Runtimes get 20 because the model keeps Qwen3-VL's architecture, which Transformers, vLLM, SGLang and llama.cpp run in released versions, while LM Studio's catalogue has only the base. Builds score 0, as NVIDIA publishes no quantised build of the 2B. The NVIDIA Open Model License allows free commercial use under a use policy (10). The gate is an automatic click-through that needs an account (5), and nothing hosts the 2B (0).
Hy-Memory-30B-A3B 85
Memory 25, Tencent's own Q4_K_M GGUF is 18.24 GB, and 18.24 GB × 1.2 = 21.9 GB, which fits 24 GB but not 16 GB. Its Q3_K_M file and the two files with experts at 1 or 2 bits are below 4-bit precision and don't count. Runtimes 20, hy_v3 model code in released vLLM (HYV3ForCausalLM in the v0.33.0 registry), SGLang v0.5.23 (hunyuan_v3.py), Transformers v5.22.2 and llama.cpp b12242, 5 each. Builds 15, Tencent publishes an FP8 repository and a GGUF repository with Q4_K_M, Q6_K and Q8_0 files in its own organisation, so quantised builds at two precisions or more. Terms 15, Apache 2.0, with only a preamble naming Tencent as copyright holder above the licence text. Download 10, gated is false for the main, FP8 and GGUF repositories on 10 November 2026, so the files download with no account or terms to accept. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026), and the card names no API. 25 + 20 + 15 + 15 + 10 + 0 = 85.
Score by category
| Category | Weight this run | Cosmos-Reason2-2B | Hy-Memory-30B-A3B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 85 | Hy-Memory-30B-A3B +20 |
| Risk | 20%20 | 60 | 60 | even |
| Agent interface | 10%10 | 65 | 65 | even |
| Documentation and upkeep | 10%10 | 39 | 68 | Hy-Memory-30B-A3B +29 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 59.5/100 | C 61/100 |
Facts side by side
| Fact | Cosmos-Reason2-2B | Hy-Memory-30B-A3B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | Tencent (Hy 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 | 2026-10-16 |
| Terms last updated | 2025-10-24 | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | yes | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | 2.5/5 (4) | none |
Verdicts
Cosmos-Reason2-2B
A small local model 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.
Hy-Memory-30B-A3B
A specialist that writes an agent's long-term memory, built to slot into Mem0, MemOS or Tencent's own framework in place of a general model. It fits a 24 GB card from Tencent's own GGUF, under plain Apache 2.0, and Tencent answers on the repository. Its results are Tencent's own and nobody has rerun them.
Before you call either
Cosmos-Reason2-2B
- Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading
- 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 - 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 - Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off
- For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply
- 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
- Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks
Hy-Memory-30B-A3B
- Use it as the writer model in Mem0, MemOS or Hy-Memory, not as the model that answers the user
- Start it with
llama-server -hf tencent/Hy-Memory-30B-A3B-GGUF:Q4_K_M --jinja, or with vLLM under the served name hy-memory as the card does - Pass
reasoning_effortas no_think inchat_template_kwargsand temperature 0, as the card's example does - Ask for a JSON object in the system prompt and validate it yourself, since no schema constraint is documented
- Treat what it stores as unverified. It keeps what a conversation says, true or not
Questions
Which is better for AI agents, Cosmos-Reason2-2B or Hy-Memory-30B-A3B?
Hy-Memory-30B-A3B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 2 of 4 scored categories.
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Machine-readable
- This page as Markdown
/compare/cosmos-reason2-2b-vs-hy-memory-30b-a3b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/cosmos-reason2-2b.json·/api/v1/tools/hy-memory-30b-a3b.json - From a terminal
anchor compare cosmos-reason2-2b hy-memory-30b-a3b(the CLI) - Over MCP
compare_tools {"a": "cosmos-reason2-2b", "b": "hy-memory-30b-a3b"}at/mcp, no key