The mysterious Hy3 LLM is topping OpenRouter Model Rankings by a large margin
A little-known Tencent large language model called Hy3 is suddenly topping OpenRouter’s usage rankings, raising questions about whether its popularity comes from genuine quality, aggressive pricing, or heavy use by a few high-volume apps. Commenters examine how OpenRouter’s token-based leaderboards can be skewed by free tiers, caching strategies, and large “whale” users, and compare Hy3’s real-world performance against models from Anthropic, Google, and DeepSeek. The conversation also highlights concerns over data privacy, jurisdiction, and contractual guarantees when sending sensitive business data to opaque or foreign AI providers accessed through aggregators like OpenRouter.
Pricing, Caching, and OpenRouter Economics
- Hy3 is popular partly because it’s very cheap on OpenRouter and “good enough” in quality for many workloads.
- DeepSeek V4 Flash can be even cheaper if used via DeepSeek’s own API due to stronger caching discounts; using it through OpenRouter can lose significant savings.
- Within OpenRouter, effective price varies by provider due to different input/output/cache pricing, so “cheapest” depends on workload mix.
- There’s confusion over why some providers are cheaper than DeepSeek itself; one explanation is that cheaper tiers use lower-precision quantization (fp4/fp8) while DeepSeek’s own endpoint may be unquantized.
- OpenRouter also offers a “Response Caching” feature for identical requests at no cost, though some question how often identical requests occur in practice.
Usage Rankings and Market Signal Quality
- OpenRouter leaderboards reflect only traffic through OpenRouter, so they underrepresent models where many users go direct (e.g., Anthropic).
- Some argue the rankings are still a valid market signal; others emphasize that a single large app (“whale”) can dominate tokens, making it hard to infer broad user preference.
- Requests for better metrics include unique-user indicators, spend-based charts, and token volume over time.
- It’s noted that a single SaaS product can burn billions of tokens per day, reinforcing that token volume ≠ number of users.
Hy3 Popularity, Performance, and “Mystery”
- Hy3 is from Tencent, so several commenters question why it’s labeled “mysterious”; others suggest the mystery is more about its sudden leaderboard dominance and deployment details.
- One commenter reports multi-benchmark testing where Hy3 ranks mid-pack among ~25–80 models, suggesting it’s not top-tier but competitive.
- Another user found it poor for coding/agentic tasks compared to newer frontier models and even strong local models, citing thought loops and undesired edits.
- Others find it attractive as a post-training base: good factual knowledge, with issues more on agent behavior than core capabilities.
- A link notes Hy3 started as a >400B parameter model later reduced to ~295B as an “optimal zone.”
Free Access and Usage Spikes
- Debate over whether Hy3’s ranking is inflated by free access.
- Some insist usage stayed high after the free period; others point out it’s still free in various apps and via a “free” OpenRouter endpoint, so the true paid-only demand is unclear.
Data Privacy, Trust, and Jurisdiction Concerns
- Some are wary of sending sensitive business data to an LLM whose developers or jurisdiction they don’t fully trust, especially with state-linked entities.
- Others argue what matters is the inference provider’s data-handling policies (e.g., zero data retention, opt-out of training), which OpenRouter claims to control via contracts.
- Skeptics question how such contracts can be verified or enforced and note that both model developers and hosts are potential threat vectors.
- There is broader unease about major US and Chinese AI companies’ relationships with their respective governments and the opacity around data use.