Models/Kolibri 1 · BF16

Agents / Aleph Alpha

Kolibri 1 · BF16

An open-weight English/German reasoning and tool-calling model with a publisher-maintained vLLM plugin and multi-GPU serving instructions.

Verified sourceReleased Oct 3, 2026Source checked 10/14/2026

LOCALRENTED GPUOPEN WEIGHTS

Freshness 95 out of 100. Release age: 12 days old, Oct 3, 2026. Measures age, not quality.

Popularity 45 out of 100. 2,254 downloads in 30 days; 60 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source

Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

WORKFLOWS FOR THIS MODEL 1

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AI agent

Build a private AI agent with Kolibri 1

Serve Kolibri 1 · BF16 privately, connect Hermes to the model endpoint, and have the agent inspect files and produce a review checklist.

Freshness 95 out of 100. Release age: 12 days old, Oct 3, 2026. Measures age, not quality.

Hermes AgentAleph Alpha vLLM plugin

1 packageLinux

Open agent guide

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At a glance

Parameters: 78B total · 3.46B active
Architecture: Mixture of experts
Context length: 262,144 recommended; up to 1,048,576 documented
License: Apache 2.0
Software: Aleph Alpha inference plugin, vLLM

MY HARDWARE

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Best for

Private bilingual reasoning endpoint.
Agentic tool use on a rented or owned multi-GPU Linux server.

Tradeoffs

Requires substantial accelerator memory; active parameter count does not make it a consumer-GPU model.
A 1M-token context is documented, but the publisher recommends no more than 262K for serving efficiency and complex tasks.

Ways to run it

Aleph Alpha inference plugin + vLLM · Linux multi-GPU server; Windows and macOS can connect as clients

Publisher lists minimum 4× A100 80 GB, 4× H100 SXM5, 2× H200, 1× B200 or 1× B300; recommended configurations differ. Start with short context and compare rental availability.

vllm serve Aleph-Alpha/Kolibri-1-BF16 --reasoning-parser kolibri1 --tool-call-parser kolibri1 --enable-auto-tool-choice

Official instructions

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AGENTSREASONINGTOOL CALLINGGERMANENGLISHVLLM

REFERENCE LIBRARY

Sources and files

Primary sources and files behind this model page.

2 SOURCES

01Aleph Alpha model card, hardware and servinghuggingface.co 02Inference plugingithub.com

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MODEL SIZE2.8T total · 104B active

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Repository opened Jun 13, 2026

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