Making efficiency-first LLMs & Applications.
Joined February 2025
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🚨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…
📷 Same prompt. Same hardware. Who gets there first?
ThinkingCap: Gemma-4-26B-A4B vs. the original, head to head on:
🌟Astrophysics: multiple-choice science
🐍Python: coding
📐Geometry: competition maths
🧬Biology: multiple-choice science
Release hat-trick 🚀🚀🚀 3 releases in 3 days!
ThinkingCap isn't just for Qwen. It works across model families, from Alibaba's Qwen to NVIDIA and Google:
Day 1 → NVIDIA Nemotron-3.5-Lightning-30B-A3B
x.com/BottleCapAI/status/211…
Day 2 → Qwen3.8-Flash-Next
x.com/BottleCapAI/status/211…
Day 3 → Google Gemma-4-26B-A4B (you're here)
Need even fewer thinking tokens? ThinkingCap PRO goes further, tuned to your workload. 📧 enterprise[at]bottlecapai[dot]com
🚨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…
BottleCapAI retweeted
🚨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…
🚨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…
BottleCapAI retweeted
🚨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…
🚨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…
🏢 Want a variant tuned for your own workload, proven on your own evals, or access to our better internal model?
Contact us at enterprise [at] bottlecapai.com
We made for all interested researchers new open task, the ThinkingCap Test 👉 github.com/BottleCapAI/Think…
Details: bottlecapai.com/careers/natu…
BottleCapAI 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…
🚨 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…
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…
