Hydrogen-1.0 vs Kimi K3: Which Should You Use?

Official Hydrogen-1.0 hero figure from the ungated NVFP4 sibling card — deep-principle/Hydrogen-1.0-NVFP4 assets/hydrogen-official-hero.png. Source · License: MIT (NVFP4 LICENSE).

Hugging Face social thumbnail for moonshotai/Kimi-K3, used to identify the open-weight card — Hugging Face social thumbnail for moonshotai/Kimi-K3. Source · License: Hugging Face card social image.

Verdict. Pick Hydrogen-1.0 if you want Deep Principle’s MIT scientific text MoE (753B, 1M / 128K max output) post-trained from GLM-5.3, and can accept a gated BF16 download (NVFP4/MXFP4 siblings were ungated on this check). Pick Kimi K3 if you want Moonshot’s ungated 2.8T/104B multimodal MoE and can accept the Kimi K3 License (MaaS revenue threshold). The blog’s FrontierScience-Research / GPQA-Diamond sentences stay vendor. We have no sourced bake-off.

Compare Hydrogen-1.0 and Kimi K3.

Dimension	Hydrogen-1.0	Kimi K3	Source
License	MIT (NVFP4 LICENSE file + BF16 card tag)	Kimi K3 License (SPDX other; MaaS + display conditions)	NVFP4 LICENSE (2026-11-03) / Kimi K3 LICENSE (2026-10-19)
Gating	BF16 gated (auto); NVFP4 and MXFP4 ungated	No	Hugging Face API
Developer	Deep Principle	Moonshot AI	Official cards
Parameters	753B (HF); active count not printed on the Hydrogen card	2.8T total / 104B activated (README); HF safetensors ~2.78T	Hugging Face API / official cards
Architecture	glm_moe_dsa; post-trained from GLM-5.3	Stable LatentMoE; MoonViT-V2 vision encoder	Official cards
Modalities	text-generation (text only)	image-text-to-text (text, image; video named in the introduction)	Hugging Face API / Hydrogen chat template
Context length	1M tokens; max output 128K (card)	1,048,576	Official cards
Serving named	SGLang tp 8 (BF16); NVFP4 8× B300; keep generation_config.json	vLLM / SGLang (card); MXFP4 weights / MXFP8 activations	Official cards
Hugging Face likes	136 on the BF16 card (2026-11-03)	11,761 on the BF16 card (2026-10-19)	Hugging Face API
Quality vs ChatGPT	Not independently tested	Not independently tested	n/a

When to choose which

MIT scientific text checkpoint post-trained from GLM-5.3: Hydrogen-1.0 — Card and blog. BF16 is gated. Not a quality rank versus Kimi K3.
Ungated 2.8T-class multimodal open weights: Kimi K3 — Image-text-to-text. License is not MIT/Apache.
Apache-or-MIT multimodal already on this site: neither — GLM-5.3-Flash is MIT 320B/18B multimodal. Different job from Hydrogen’s text science card.
Published laptop-class GGUF path: neither — Both cards we opened are datacenter-class. No Hydrogen GGUF sibling named here.

Read the entity pages: Hydrogen-1.0 and Kimi K3. Both hang off ChatGPT alternatives and closed LLM APIs.

Why this comparison exists

Deep Principle’s 2 November 2026 blog names Kimi-K3 as the open frontier reference on its science evals. This site already has a Kimi K3 identification page. Hydrogen is a gated MIT 753B text science post-train of GLM-5.3; Kimi K3 is an ungated 2.8T multimodal MoE under a custom license. Identification, not a bake-off.

Sourced snapshot (Hydrogen 2026-11-03 / Kimi K3 2026-10-19)

Field	Hydrogen-1.0	Kimi K3
Host	huggingface.co/deep-principle/Hydrogen-1.0 (`gated: auto`)	huggingface.co/moonshotai/Kimi-K3 (not gated)
HF likes	136 (BF16, 2026-11-03)	11,761 (2026-10-19)
License	MIT (NVFP4 LICENSE file)	Kimi K3 License (SPDX other)
Size	753B (HF); active count not printed	2.8T / 104B
Job	text-generation (science assistance)	image-text-to-text
Context	1M; max output 128K	1,048,576
Official serve path	SGLang tp 8; keep generation_config.json	vLLM / SGLang (card)
Quant siblings	NVFP4 (ungated), MXFP4 (ungated)	MXFP4 / MXFP8 (lead card)
Quality vs ChatGPT	Not independently tested	Not independently tested

License

Hydrogen NVFP4 LICENSE is MIT. Kimi K3 LICENSE is the Kimi K3 License with a USD 20 million MaaS agreement trigger. Not legal advice.

How to choose

Need MIT scientific text post-trained from GLM-5.3: Hydrogen-1.0.
Need ungated 2.8T multimodal and can accept the Kimi K3 License: Kimi K3.
Need Z.ai’s MIT 320B/18B multimodal Flash SKU: GLM-5.3-Flash.
Need Apache-2.0 35B science/agent VLM: Sage-A1.5.

FAQ

Which is easier to download?

Kimi K3 is ungated. Hydrogen BF16 is gated: auto. Hydrogen NVFP4 and MXFP4 were ungated on 2026-11-03. We have not measured either VRAM.

Did Hydrogen beat Kimi K3 on GPQA-Diamond?

The 2 November 2026 Deep Principle blog says Hydrogen improves over GLM-5.3 on GPQA-Diamond in their evaluations, roughly matching Kimi-K3. That is vendor/self-reported. We do not copy numeric scores from the blog figure.

Are both MIT?

Hydrogen NVFP4 LICENSE is MIT. Kimi K3 License is not MIT/Apache (MaaS revenue threshold). Not legal advice.

Why isn’t this Hydrogen vs GLM-5.3-Flash?

Hydrogen’s named base is GLM-5.3, not Flash. GLM-5.3-Flash is a 320B/18B multimodal SKU already on this site. The blog compares Hydrogen with Kimi K3 on science benches, so this pair hangs off two sourced entity URLs.

Sources & verification

Last verified 2026-11-03 · Last updated 2026-11-03· Edited by forkalt editors · Editorial policy

License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.