Compare/Google Gemma 4 vs Tencent Hy3-preview

AI tool comparison

Google Gemma 4 vs Tencent Hy3-preview

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

G

Open Source Models

Google Gemma 4

Google's open multimodal models — vision, audio, and text under Apache 2.0

Ship

75%

Panel ship

Community

Paid

Entry

Google Gemma 4 is the most capable open model family Google has released, and the first to unify text, vision, and audio in a single architecture — all under the Apache 2.0 license. Available in four sizes (E2B, E4B, 26B MoE, 31B Dense), the lineup runs everywhere from smartphones to high-end GPUs and covers 140+ languages with context windows up to 256K. The headline stat: the 31B Dense model benchmarks above models nearly 20x its size in certain evals, making it the sharpest intelligence-per-parameter model in the open-source ecosystem as of its April 2026 release. The multimodal architecture processes documents with OCR, analyzes charts, transcribes speech, and understands video frames from a single model — no pipeline stitching required. For developers and researchers, the Apache 2.0 licensing is the real unlock. Gemma 4 is fully OSI-approved and commercially usable without restriction, building on a community of 400M+ downloads from prior Gemma versions and 100,000+ variants in the wild.

T

AI Models

Tencent Hy3-preview

Tencent's first open-source frontier MoE — 295B params, 21B active, free on HuggingFace

Ship

75%

Panel ship

Community

Free

Entry

Tencent's Hy3-preview is the company's first public frontier-class language model, released April 23 as open weights on Hugging Face. The model is a 295B parameter Mixture-of-Experts architecture with only 21B parameters active per token — keeping inference costs comparable to much smaller dense models while reaching capabilities that compete with leading proprietary systems. The release comes under new leadership: Yao Shunyu, a former OpenAI researcher, joined Tencent in early 2026 to build out its frontier AI effort. The team claims to have gone from project start to public release in under three months — an unusually fast timeline for a model of this scale. The 256K context window and strong performance on agentic and coding benchmarks position it directly against GLM-5.1 and Qwen3.6 in the open-source frontier race. Free inference is available on OpenRouter's free tier at launch, with the model also appearing on Hugging Face's Inference API. The architecture uses 192 routed experts in a hybrid dense-MoE configuration. For teams needing a capable open-weights model for agentic workflows without paying proprietary API rates, Hy3-preview arrives as a credible option at a remarkable cost-to-capability ratio.

Decision
Google Gemma 4
Tencent Hy3-preview
Panel verdict
Ship · 3 ship / 1 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Open Source / Apache 2.0
Open Source (free on HuggingFace, free tier on OpenRouter)
Best for
Google's open multimodal models — vision, audio, and text under Apache 2.0
Tencent's first open-source frontier MoE — 295B params, 21B active, free on HuggingFace
Category
Open Source Models
AI Models

Reviewer scorecard

Builder
80/100 · ship

Apache 2.0 on a model that beats GPT-class performance at 31B? Ship it immediately. The MoE 26B variant is already running under 16GB VRAM for me with llama.cpp quantization. The unified multimodal arch saves a ton of pipeline complexity.

80/100 · ship

295B MoE with 21B active per token is a sweet spot for production use — you get frontier-quality outputs at a fraction of the compute cost. The 256K context and agent-optimized design make this immediately useful for complex workflow automation. Worth running evals against your specific use case.

Skeptic
45/100 · skip

Google's benchmark marketing is getting harder to trust — 'beats 600B rivals' is cherry-picked. The audio modality is notably weaker than Gemini 3.1, and fine-tuning the MoE variant requires infrastructure most teams don't have. Real-world performance lags the headline numbers.

45/100 · skip

Tencent hasn't published a full technical report yet, so benchmark claims are hard to independently verify. The 'three months to frontier' narrative sounds impressive but raises questions about training data sourcing and evaluation rigor. Preview releases from large Chinese labs have historically required patience before production stability.

Futurist
80/100 · ship

The 100,000-variant Gemmaverse is a real ecosystem flywheel. Every new Gemma release compresses capability curves downward — things that required cloud APIs last year now run on-device. Gemma 4's audio addition makes it the first truly comprehensive local AI.

80/100 · ship

The pace of open-source frontier models from Chinese labs is accelerating faster than anyone predicted — we now have credible open-weight competition from Alibaba, Zhipu, Xiaomi, and Tencent simultaneously. This is geopolitically significant and means the open-source ecosystem will stay competitive with proprietary models for years.

Creator
80/100 · ship

A single model that can read my documents, analyze charts, transcribe my audio notes, and generate code is genuinely transformative for creative production. The Apache license means I can embed it in client deliverables without legal headaches.

80/100 · ship

For multilingual creative work — especially for Chinese market content — having a frontier-quality open-source model from a Chinese lab is meaningful. The free OpenRouter tier means creators can experiment without API budgets.

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