Qwen3.8-Flash-Next: Time to Update Those Benchmarks
Heat trend
Collecting trend data
The percentage is based on available heat signal, not comment count or independent people.
Qwen model activity is surfacing — worth tracking for capability changes, ecosystem impact, and availability.
The Qwen 3.8 27B model, specifically the Qwen3.8-Flash-Next version, is performing well in coding benchmarks, outperforming most other models.…
it still very early, so had to disable oMLX K/V caching, qwen4_exp architectureis not yet supported + the obvious n-grams with which the whole 4 bit quant takes ~100G, so pretty tight
nevertheless, this is the first model for the year that was able to break through 94% on my cupel benchmark
one interesting bit is Qwen 3.8 27B is obviously great, but it did not do that well, since I have coding, general knowledge and science. it did outperform most in coding, but its general knowledge lost to Gemma 31B as well as to Qwen 3.6
this is the quant I tried with oMLX, which performed better than other 4 bit quants due to the mixed quantization:
this is a very good quant from Unsloth, it is not as strong as "MLX-mixed-4_8bit", but I could not fit a larger one from unsloth to be able to bench. You can see it on position #6 in the above leaderboard
I am working on collecting all I did for the last few months codingwise, and will add more pieces into the benchmark (hermes => pi / opencode, etc..) because models are getting too good to differentiate: I love it!