Agnes-3.0-Flash

Agnes-3.0-Flash Preview is the open-weight checkpoint on Hugging Face. The card is Apache-2.0, pipeline image-text-to-text, languages English and Chinese. Hugging Face listed 120 likes and 34 last-month downloads on 2026-09-13. createdAt is 2026-09-11. Safetensors total about 33.09B parameters (BF16). r/LocalLLaMA hot on 2026-09-13 titled it "Agnes-AI/Agnes-3.0-Flash 33B Multimodal, AA score: 36". Treat that AA figure as the proprietary API score, not these weights.

The card is explicit: this repo is an earlier Preview checkpoint. The production/API model on Artificial Analysis is a different checkpoint (1M context, proprietary). Do not copy API scores onto the 33B files.

Compare Qwen3.8-27B if you wanted a dense local chat SKU, Muse Glimmer if you wanted another ~30B open multimodal, or Ling-3.0-Flash if you wanted a hosted flash SKU.

Key Features

• Hybrid attention: 72 decoder layers, 3:1 gated delta-rule vs global attention. Only 18 layers keep a growing KV cache. Context on the Preview card is 262,144 tokens.
• Multimodal: text, image, and video through bundled processors. Vision tower is 27 layers, hidden 1152, patch 16.
• Reasoning effort: chat template exposes high / medium / low plus enable_thinking=False.
• Tool calling: <tool_call><function=…> blocks. SGLang serve script and patch files ship in-repo.
• Remote code: load with trust_remote_code=True. Tested path on the card is transformers>=5.12.

Limitation: 120 likes is heat, not an audit. Custom architecture needs remote code. Hardware note on the card is 1 x H200 141 GB or H100 80 GB at bf16, about 66 GB on disk. Preview vendor rows (IFBench 74.20, GPQA Diamond 85.05, SciCode 38.08) are mixed-harness reference numbers. We did not rerun them.

Specs

Use Cases

• Local multimodal boxes that can spare one H100/H200 and want Apache-2.0 weights with images and video.
• People who saw the r/LocalLLaMA 33B post and need the Preview vs API split spelled out.
• People who should call the API instead if they wanted the 1M-context proprietary SKU at $0.05 / $0.15.

If you needed a cheap hosted flash path, start with DeepSeek-V4-Flash.

Getting Started

1. Open Agnes-AI/Agnes-3.0-Flash.
2. pip install "transformers>=5.12" torch torchvision accelerate.
3. Load with trust_remote_code=True, dtype="bfloat16", device_map="auto".
4. For serving, follow serve.sh and sglang_patch/ rather than a stock public image.

First-party resource: the model card. Product site: agnes-ai.com.

Frequently Asked Questions

Is the Hugging Face repo the same model as Artificial Analysis score 36?

No. The card says Preview is 33B / 262k. AA lists a proprietary 1M-context API model. Reddit's title mixed the two.

Can I skip trust_remote_code?

No. The architecture is custom (AgnesForConditionalGeneration).

Does Preview have a 1M window?

Not on the open weights. 1M is the production/API checkpoint.

Alternatives

• Qwen3.8-27B: dense local chat without a custom remote-code stack.
• Muse Glimmer: another ~30B open multimodal on this site.
• DeepSeek-V4-Flash: hosted flash SKU if you did not want to self-host.

Tips

1. Do not paste AA Index 36 onto the 33B files.
2. Keep temperature 1.0, top_p 0.95, top_k 20 unless you remeasure.
3. Run serve.sh from the repo instead of assuming stock vLLM knows agnes.

Conclusion

Agnes-3.0-Flash Preview is the 33B Apache-2.0 multimodal dump to try if you have an H100-class box and can live with remote code. Start at the Hugging Face card, and keep the proprietary API page separate.