I build things that make me excited about the future. @BottleCapAI: AI Lab focused on efficiency & new architectures. @BeatSaber VR game (acquired by Meta).

Joined July 2012
Jaroslav Beck retweeted
One of the most interesting AI labs in Europe is being built out of Prague The team believe that frontier models drastically overthink, and therefore burn tokens unnecessarily So @BottleCapAI (named after Europe's greatest innovation) takes an existing open model and trains it to think less while staying just as accurate. Last week the lab released 3 models: >> Nvidia’s Nemotron: up to 31% and on average 23% less thinking, with comparable benchmark accuracy >> Alibaba’s Qwen3.8-Flash-Next: spending 39% fewer thinking tokens on average for about a point of accuracy loss >> Google’s Gemma 4: their first ThinkingCap on a Google model, with 39% fewer thinking tokens on average for just 0.15pp of accuracy The impact of what they're building is less token spend and less hardware is required. VERY COOL @JaroslavBeck @itsdavidherel
🚨ThinkingCap: Gemma-4-26B-A4B is out! The most token-efficient Gemma-4-26B-A4B available. 🚀Up to 69% fewer thinking tokens, 38.9% on average 🎯Negligible accuracy loss 0.15pp 🏢ThinkingCap PRO: up to 87.6% fewer thinking tokens, 62% on average - Contact our enterprise[at]bottlecapai[dot]com 📄Blogpost: bottlecapai.com/post/thinkin… 🤗Hugging Face: huggingface.co/bottlecapai/T… 🔗GGUF: huggingface.co/bottlecapai/T…
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My wife told me we’re going to a movie themed event next week and that I should find myself an introvert friendly costume… Challenge accepted.
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Jaroslav Beck retweeted
The ThinkingCap series keeps growing. Last week we released: → Nemotron 3.5 Lightning: up to 2.3x more requests served at once → Qwen3.8-Flash-Next: up to 51% fewer thinking tokens → Gemma 4 26B: up to 69% fewer thinking tokens Have fun! bottlecapai.com/#products
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Jaroslav Beck retweeted
🚨ThinkingCap: Gemma-4-26B-A4B is out! The most token-efficient Gemma-4-26B-A4B available. 🚀Up to 69% fewer thinking tokens, 38.9% on average 🎯Negligible accuracy loss 0.15pp 🏢ThinkingCap PRO: up to 87.6% fewer thinking tokens, 62% on average - Contact our enterprise[at]bottlecapai[dot]com 📄Blogpost: bottlecapai.com/post/thinkin… 🤗Hugging Face: huggingface.co/bottlecapai/T… 🔗GGUF: huggingface.co/bottlecapai/T…
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Third release in 3 days! Let's go! 🚀
🚨ThinkingCap: Gemma-4-26B-A4B is out! The most token-efficient Gemma-4-26B-A4B available. 🚀Up to 69% fewer thinking tokens, 38.9% on average 🎯Negligible accuracy loss 0.15pp 🏢ThinkingCap PRO: up to 87.6% fewer thinking tokens, 62% on average - Contact our enterprise[at]bottlecapai[dot]com 📄Blogpost: bottlecapai.com/post/thinkin… 🤗Hugging Face: huggingface.co/bottlecapai/T… 🔗GGUF: huggingface.co/bottlecapai/T…
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And a faster release cadence doesn’t mean we’re compromising on quality. Quite the opposite.
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Jaroslav Beck retweeted
We're not done yet with releases❗️ Today we are releasing the most efficient Qwen model in its category: ThinkingCap: Qwen3.8-Flash-Next.
🚨ThinkingCap: Qwen3.8-Flash-Next is out! The most token-efficient Qwen3.8-Flash-Next available. 🚀Up to 51% fewer thinking tokens, 38.5% on average 🎯Negligible accuracy loss 1.03pp 🏢ThinkingCap PRO: 60% fewer thinking tokens on average - Contact our enterprise[at]bottlecapai [dot]com 📄Blogpost: bottlecapai.com/post/thinkin… 🤗Hugging Face: huggingface.co/bottlecapai/T… 🔗GGUF: huggingface.co/bottlecapai/T…
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We're not done yet with releases❗️ Today we are releasing the most efficient Qwen model in its category: ThinkingCap: Qwen3.8-Flash-Next.
🚨ThinkingCap: Qwen3.8-Flash-Next is out! The most token-efficient Qwen3.8-Flash-Next available. 🚀Up to 51% fewer thinking tokens, 38.5% on average 🎯Negligible accuracy loss 1.03pp 🏢ThinkingCap PRO: 60% fewer thinking tokens on average - Contact our enterprise[at]bottlecapai [dot]com 📄Blogpost: bottlecapai.com/post/thinkin… 🤗Hugging Face: huggingface.co/bottlecapai/T… 🔗GGUF: huggingface.co/bottlecapai/T…
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Jaroslav Beck retweeted
ThinkingCap version of NVIDIA Nemotron3.5 Lightning is out. Have fun!
🚨ThinkingCap: NVIDIA Nemotron3.5 Lightning30B A3B is out! ⚡️Up to 2.3x more requests for multi user use compared to original Nemotron version. 🚀 Up to 31%, on average 23% fewer thinking tokens 🎯 Minimal accuracy loss - 0.88pp 📄 Blogpost: bottlecapai.com/post/thinkin… 🤗 Hugging Face: huggingface.co/bottlecapai/T… 🔗 GGUF: huggingface.co/bottlecapai/T…
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ThinkingCap version of NVIDIA Nemotron3.5 Lightning is out. Have fun!
🚨ThinkingCap: NVIDIA Nemotron3.5 Lightning30B A3B is out! ⚡️Up to 2.3x more requests for multi user use compared to original Nemotron version. 🚀 Up to 31%, on average 23% fewer thinking tokens 🎯 Minimal accuracy loss - 0.88pp 📄 Blogpost: bottlecapai.com/post/thinkin… 🤗 Hugging Face: huggingface.co/bottlecapai/T… 🔗 GGUF: huggingface.co/bottlecapai/T…
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Právě v čas. Za chvíli nahráváme Fantastic Future Pod!
Do a kickflip!
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… mam?
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Ok. I am that type of person who instead of cleaning kitchen spends that time by cleaning training data for my humanoid Jarmil to do autonomously. Of course my wife is equally excited as me…
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Jaroslav Beck retweeted
🚨 Same model size. Same GPU. ~4.7x more work done! ThinkingCap: Qwen 3.8 reaches answers with about half the reasoning. On a shared server, that means 2x more users fit in memory at once, and each finishes 2x faster. Running it solo? ~2x faster answers. Serving a team? ~4.7x throughput. 🚀 🤗 Hugging Face: huggingface.co/bottlecapai/T…
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Jaroslav Beck retweeted
ThinkingCap: Qwen3.8-27B now runs on a Mac and fits a 32GB machine! 4-bit MLX build - 21 GB, down from 52 GB Performance is very close to the full precision version. Vision capabilities and MTP speculative decoding are kept. huggingface.co/bottlecapai/T…
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Jaroslav Beck retweeted
The legends pulling off the ThinkingCap release in record time💪🙏
🤖 Made with AI
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Actually we were very busy with another big project in works, but I am glad we finally got some time to polish Qwen 3.8 27b with our ThinkingCap. A lot positive feedback so far!🙏
🚨ThinkingCap: Qwen3.8-27B is out! The most token-efficient Qwen3.8 27B available, this time optimized for agentic use. 🚀 Up to 65% fewer thinking tokens, 37% on average 🎯 Minimal accuracy loss 📈 Long-context retrieval actually went up 2.3pp 📄 Blogpost: bottlecapai.com/post/thinkin… 🤗 Hugging Face: huggingface.co/bottlecapai/T… 🔗 GGUF: huggingface.co/bottlecapai/T…
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Jaroslav Beck retweeted
Side by side comparison
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