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Tiny Aya Water

Tiny Aya Water is a 3.35B-parameter multilingual language model optimized for European and Asia Pacific languages. It uses a 36-layer transformer with 2,048 hidden size, 16 attention heads, and 4 KV heads. The architecture interleaves sliding window attention (4,096 window) with periodic global attention layers for efficient long-range interaction. It supports around 8K context length and uses RoPE for positional encoding. Trained across 70+ languages, it is designed for strong regional performance while remaining efficient for local deployment and downstream adaptation.

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About this model

PaperBlogHF Model Card

Tiny Aya Water is a 3.35B-parameter multilingual language model optimized for European and Asia Pacific languages. It uses a 36-layer transformer with 2,048 hidden size, 16 attention heads, and 4 KV heads. The architecture interleaves sliding window attention (4,096 window) with periodic global attention layers for efficient long-range interaction. It supports around 8K context length and uses RoPE for positional encoding. Trained across 70+ languages, it is designed for strong regional performance while remaining efficient for local deployment and downstream adaptation.

Model Type

Dense LLM

Released

February 17, 2026

License: CC-BY-NC-4.0

Parameters

3B

Model ID
CohereLabs/tiny-aya-water
Capabilities
Text GenerationInstruction FollowingText ClassificationMultilingual

Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (CohereLabs/tiny-aya-water). Released under CC-BY-NC-4.0. Further reading: Paper · Blog

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Hardware

MI325X

2,048 GB

B200

1,440 GB

Engine

vLLM
SGLang

Deployment code

INFERENCE COMMAND
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Performance under load

57k46k34k23k11k011664128256512Total Tokens / secConcurrent requests
Tokens/s (total)

Benchmarks measured by Vultr on MI325X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.

SS

Shivam Sharma

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