Tencent @TencentHunyuan dropped the non-preview version of Hy3 and changed their license from the community one (restrictive + not allowed in SK, UK, EU) to Apache 2.0!!! 🙏
Tencent releases its 295B Hunyuan3 MoE model under an Apache 2.0 license, lifting regional access limits
The model matches larger systems on SWE-bench and GPQA Diamond.
Positive users praise Tencent's Hy3 model and its Apache 2.0 open licensing as meaningful progress for open AI, while negative users call the model disappointing at coding or inferior to alternatives like GLM.
No Digg Deeper questions have been answered for this story yet.
Most Activity
If these scores are real, Tencent has just become one of the leaders of open source. Hy3 is a 295B 21AB model that at least beats GLM 5.1 in blind tests. Might even warrant architecture transition (it's a basic GQA). Good job.
Tencent @TencentHunyuan dropped the non-preview version of Hy3 and changed their license from the community one (restrictive + not allowed in SK, UK, EU) to Apache 2.0!!! 🙏
new open (apache 2.0!) model from @TencentHunyuan, Hy3 is only 295B total 21B active and competitive with MUCH bigger model on benchmarks
https://huggingface.co/tencent/Hy3
the benchmark scores are REALLY crazy for a 300B model
new open (apache 2.0!) model from @TencentHunyuan, Hy3 is only 295B total 21B active and competitive with MUCH bigger model on benchmarks
https://huggingface.co/tencent/Hy3
Ohh this looks incredibly promising. Time to throw some internal evals at it . If it's performance is even moderately close to it's published evals, this could be a really great model
Tencent @TencentHunyuan dropped the non-preview version of Hy3 and changed their license from the community one (restrictive + not allowed in SK, UK, EU) to Apache 2.0!!! 🙏
Pretty strong model from Tencent
If these scores are real, Tencent has just become one of the leaders of open source. Hy3 is a 295B 21AB model that at least beats GLM 5.1 in blind tests. Might even warrant architecture transition (it's a basic GQA). Good job.

@Jaidcel @TencentHunyuan Yes! https://huggingface.co/tencent/Hy3
from the model card seems to not only be benchmark
> We don't think public benchmark scores tell the full story. So we ran a blind test with 270 experts from various disciplines, working on real-world workflows, and collected 312 valid comparisons. Hy3 scored 2.67/4, outperforming GLM-5.1 at 2.51/4. The advantage was clearest in frontend development, CI/CD, and data & storage.
new open (apache 2.0!) model from @TencentHunyuan, Hy3 is only 295B total 21B active and competitive with MUCH bigger model on benchmarks
https://huggingface.co/tencent/Hy3

@teortaxesTex doesn't have 1M context! model without sparse attention is ok at 256k (also you can do GQA -> MSA)

@eliebakouch There are ways to convert GQA to MLA and therefore to DSA I mean that this model is strong but with the current baselines not economical for long sequences

@xeophon @TencentHunyuan Updated weights?
@teortaxesTex Some truly insane jumps, especially for this size
If these scores are real, Tencent has just become one of the leaders of open source. Hy3 is a 295B 21AB model that at least beats GLM 5.1 in blind tests. Might even warrant architecture transition (it's a basic GQA). Good job.
@teortaxesTex wdym? > Might even warrant architecture transition (it's a basic GQA)
If these scores are real, Tencent has just become one of the leaders of open source. Hy3 is a 295B 21AB model that at least beats GLM 5.1 in blind tests. Might even warrant architecture transition (it's a basic GQA). Good job.

@xeophon @TencentHunyuan >not allowed in SK, UK, EU

@xeophon you consistently naming and shaming non apache releases as soon as they come out has probably had a non negligible impact on the state of open models, good job

@din0s_ haha, idk how much of an impact it really has, i just don't want to deal with reading licenses :(

@eliebakouch @TencentHunyuan Wow, it has improved a lot from preview.
Makes me even more excited about deepseek v4 non-preview release

@eliebakouch @TencentHunyuan only 295B

@eliebakouch why would you take an average across different benchmarks? that doesn’t seem very scientific.

@paradite_ This is just a quick visualization I asked Claude to make while on the plane lol, but how would you combine scores from a pool of benchmark of the same domain?
@_xjdr Please share the result 🫡
Ohh this looks incredibly promising. Time to throw some internal evals at it . If it's performance is even moderately close to it's published evals, this could be a really great model