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Kolibri-1

Aleph-Alpha

Kolibri is Aleph Alpha's mixture-of-experts (MoE) reasoning model, with a focus on German and English. The model supports an explicit reasoning mode and tool calling. It is optimized for long-context and inference efficiency. Kolibri is intended to process text input and output in German and English and to perform a wide range of tasks beyond natural-language generation, for example multi-step reasoning, coding, structured extraction, retrieval-augmented generation, long-document processing and agentic tool calling. Kolibri was pre-trained on sequences of 16,384 tokens, mid-trained on 65,536 and trained on 262,144 tokens in a final long-context phase, which is its native context length. Because positional encoding is applied only in the sliding-window layers, the context can be extended beyond that length without any position scaling, in principle to arbitrary lengths. We have validated quality and serving efficiency up to 1,048,576 tokens. For latency- or throughput-sensitive deployments and for complex tasks, we recommend contexts of at most 262,144 tokens. See the technical report for details.

Text generation

Input Text→ Output Text

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Kolibri-1-BF16

Aleph-Alpha

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Text generation

Input Text→ Output Text

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Pharia-1-LLM-7B-control-hf

Aleph-Alpha

This is the safetensors-conversion of `Pharia-1-LLM-7B-control`. We provide a joint model card for `Pharia-1-LLM-7B-control` and `Pharia-1-LLM-control-aligned`. Find this model card here.

Text generation

Input Text→ Output Text

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Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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Explore AI models 3

Kolibri-1

Kolibri-1-BF16

Pharia-1-LLM-7B-control-hf

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