Models / Kolibri 1

Kolibri 1

MoE premier
  **The sovereign European MoE, one year after it needed a state subsidy to exist.** Aleph Alpha shipped Kolibri 1 on October 3, 2026 (German Unity Day): 78B total parameters, 3.46B active per token, trained on a 20T-token bilingual corpus (62.5 percent English, 23.9 percent German, 13.6 percent code). Apache-2.0 weights on Hugging Face; the company is an EU GPAI Code of Practice signatory and markets the release as the first sovereign European open-weight MoE.

  **The architecture is the efficiency story.** 50 layers split 40 sliding-attention (513-token window) to 10 full-attention; positional encoding lives only in the sliding layers, so the context extends to 1,048,576 tokens without the KV cache exploding: the 10 full-attention layers run about 20.5MB per 1,000 tokens at fp16 and the 40 sliding layers cap at roughly 21MB fixed, so a 256k-token context holds about 5.3GB of cache. MoE 384 experts with 6 active plus one shared expert on a 2,560 hidden size.
coding agentic reasoning multilingual long-context
Context
1048k
License
apache 2.0
Developer
Aleph Alpha
Released
Oct 2026

Scores

Coding
62
Reasoning
68
Tool calling
66
General
54

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Run it locally

Per-quant memory needs and a static "can you run it?" reference - no rig entry required

BF16
156.2GB 156.2GB min 187.0GB rec
Full quality, largest

The reference hardware

Schematic of the NVIDIA Jetson Orin NX 16GB reference rig - 16GB unified memory, 102 GB/s aggregate bandwidth
Schematic of the Jetson AGX Orin 64GB reference rig - 64GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Single GTX 1080 Ti (11GB) reference rig - 11GB VRAM, 484 GB/s aggregate bandwidth
Schematic of the Single RTX 4090 (24GB) reference rig - 24GB VRAM, 1008 GB/s aggregate bandwidth
Schematic of the Single RTX 5090 (32GB) reference rig - 32GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the RTX PRO 6000 Blackwell (96GB) reference rig - 96GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the 2x RTX 3090 (48GB) reference rig - 48GB VRAM, 1872 GB/s aggregate bandwidth
Schematic of the 2x RTX 5090 (64GB) reference rig - 64GB VRAM, 3584 GB/s aggregate bandwidth
Schematic of the 4x RTX 4090 (96GB) reference rig - 96GB VRAM, 4032 GB/s aggregate bandwidth
Schematic of the 4x RTX 5090 (128GB) reference rig - 128GB VRAM, 7168 GB/s aggregate bandwidth
Schematic of the MacBook Pro M5 Max 128GB reference rig - 128GB unified memory, 614 GB/s aggregate bandwidth
Schematic of the Ryzen AI Max+ 395 128GB reference rig - 128GB unified memory, 256 GB/s aggregate bandwidth
Schematic of the DGX Spark 128GB unified reference rig - 128GB unified memory, 273 GB/s aggregate bandwidth
Schematic of the 4x H100 80GB (320GB) reference rig - 320GB VRAM, 13400 GB/s aggregate bandwidth
Schematic of the NVIDIA DGX Station 748GB reference rig - 748GB unified memory, 8000 GB/s aggregate bandwidth
Schematic of the 8x RTX 3090 rack (192GB) reference rig - 192GB VRAM, 7489 GB/s aggregate bandwidth
Schematic of the AMD Instinct MI300X (192GB) reference rig - 192GB VRAM, 5324 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 192GB reference rig - 192GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 512GB reference rig - 512GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Dual EPYC 9004 + 768GB DDR5-4800 reference rig - 768GB unified memory, 460 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-3200 + 2x RTX 3090 reference rig - 560GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-2400 + 2x RTX 3090 reference rig - 560GB unified memory, 153 GB/s aggregate bandwidth

22 reference configs, drawn in-house. Scroll for more.

Can you run it? - reference rigs

Rig BF16
NVIDIA Jetson Orin NX 16GB no -> cloud
Jetson AGX Orin 64GB no -> cloud
Single GTX 1080 Ti (11GB) no -> cloud
Single RTX 4090 (24GB) no -> cloud
Single RTX 5090 (32GB) no -> cloud
RTX PRO 6000 Blackwell (96GB) offload
2x RTX 3090 (48GB) no -> cloud
2x RTX 5090 (64GB) no -> cloud
4x RTX 4090 (96GB) offload
4x RTX 5090 (128GB) offload
MacBook Pro M5 Max 128GB no -> cloud
Ryzen AI Max+ 395 128GB no -> cloud
DGX Spark 128GB unified no -> cloud
4x H100 80GB (320GB) fast 47.2t/s
NVIDIA DGX Station 748GB fast 28.2t/s
8x RTX 3090 rack (192GB) fast 26.4t/s
AMD Instinct MI300X (192GB) ok 18.7t/s
Mac Studio M4 Ultra 192GB slow 4.2t/s
Mac Studio M4 Ultra 512GB slow 4.2t/s
Dual EPYC 9004 + 768GB DDR5-4800 slow 1.6t/s
Epyc + 512GB DDR4-3200 + 2x RTX 3090 slow 0.7t/s
Epyc + 512GB DDR4-2400 + 2x RTX 3090 slow 0.5t/s

Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.

Download options

BF16 official
156.2GB dl 156.2GB min 187.0GB rec
REC RAM vs largest quant
156.2GB bf16 weights (safetensors file sum) + KV at 20.5MB per 1k tokens (full-attn layers only); ~187GB to serve at 256k

Or run it in the cloud

No per-token API provider pricing tracked for Kolibri 1 yet. For flagship list prices, see the calculator.

PRICE HISTORY

Inference cost over time

Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.

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