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Today we’re announcing our “ThinkingCap” efficient model series with a 2× thinking token reduction on average in Qwen 3.6 27B, with up to 10x faster generation on individual examples.

51,640 views • 3 months ago •via X (Twitter)

26 Comments

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

The results across seven out-of-domain benchmarks: 🏆 Up to 10x faster in specific responses 📉 ~46% fewer reasoning tokens on average 🎯 −0.7pp accuracy difference (comparable accuracy) 🔄 Fewer reasoning loops & dead-ends ⚡ Lower latency, lower inference cost, better real-world throughput

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

I am using this improved model in my local cluster “Bob” for some time now. I’s fast and also shortening the answers without degrading the output.

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

Our goal was to get to same answer sooner with fewer tokens burned and without loosing accuracy.

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

🔗 Full technical write-up with methodology & numbers in our blog post: 🔗 HuggingFace LINK:

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

PS: Efficiency not just in open models is our core thesis since we started year ago. If you want to work on frontier of efficiency, join us!

Martin Havel's profile picture
Martin Havel3 months ago

Replicated on Czech-language RAG (tender docs, 3090, same quants): −29–55 % thinking, 0 quality loss, and 3× lower variance in thinking length across seeds — more predictable latency in production. Fits 24GB. Well done 👏

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

🔥

Tom Krcha's profile picture
Tom Krcha3 months ago

🏎️ love it!

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

🙌🔥

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

;)

Chetin's profile picture
Chetin3 months ago

Interesting.

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

your 🤖 Henry would love this model!

Ondřej Súkup's profile picture
Ondřej Súkup3 months ago

Any plan for official mlx ?

Ddddddd's profile picture
Ddddddd3 months ago

Qwen 3.6 36b-A3 will work also?

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

Our training algorithm will work for most open models.

Jan Kozák 🇨🇿🇪🇺🇺🇦🇵🇱's profile picture
Jan Kozák 🇨🇿🇪🇺🇺🇦🇵🇱3 months ago

i will wait for mtp, this is currently slower

Gedeon's profile picture
Gedeon3 months ago

Good stuff

Latent Node's profile picture
Latent Node3 months ago

Great idea, similar to autothink - ?

Adel Bucetta's profile picture
Adel Bucetta3 months ago

what makes the 2x token reduction so remarkable is it's a direct result of rethinking compute and dataflow from scratch

Pavol Zajicek's profile picture
Pavol Zajicek3 months ago

Interesting 👍 Does it support MTP?

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

Yep

Pavol Zajicek's profile picture
Pavol Zajicek3 months ago

Can I make Beat Saber 2 with it? 🙃✌️

Jaroslav Beck's profile picture
Jaroslav Beck3 months ago

Go ahead! ;)

Johnny Hu's profile picture
Johnny Hu3 months ago

Pitty it's at the beginning of summer holidays, tried to promote it to a community neewsfeed but everyone is gone for weeks :(. But thanks for making europe great again 😁 keep rocking

smeekky's profile picture
smeekky3 months ago

Great job, @JaroslavBeck ! Keep up the excellent work. You are truly inspiring, and the Czech Republic appreciates what you do more than it may seem at first glance. Thank you to your entire team.

Václav Knapp's profile picture
Václav Knapp3 months ago

Really cool guys!! 🇨🇿🇨🇿🔥 I have 4 questions below👇

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