Vikhr Nemo 12B Instruct R 21 09 24

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released September 20241024K context≈ 768,000 words12B params

A Russian-language specialist built on a 12B parameter base, Vikhr Nemo focuses on instruction-following with a notably large context window of 1 million tokens — meaning it can hold enormous amounts of text in working memory at once. It's an open-weight model, so the weights are freely available for self-hosting and fine-tuning. Details about its specific capability profile beyond Russian-language instruction tuning are limited from available data.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Reasoning & Logic

Vikhr Nemo 12B Instruct R 21 09 24

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released September 20241024K context≈ 768,000 words12B params

A Russian-language specialist built on a 12B parameter base, Vikhr Nemo focuses on instruction-following with a notably large context window of 1 million tokens — meaning it can hold enormous amounts of text in working memory at once. It's an open-weight model, so the weights are freely available for self-hosting and fine-tuning. Details about its specific capability profile beyond Russian-language instruction tuning are limited from available data.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Reasoning & Logic

Glossary

Capability profileA structured assessment of what a model can and cannot do across different dimensions like operations or visual targets.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Fine-TuningThe process of further training a pre-trained model on new data to adapt it for specific tasks or domains.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.Open-Weight ModelA model whose trained weights are publicly released, allowing anyone to download and run it locally.Self-HostingRunning a model on your own hardware or servers instead of relying on a company's cloud service.TokensThe basic units of text that a language model processes, typically representing words or word fragments.WeightsThe numerical parameters inside a neural network that determine how it processes input and generates output.

Capabilities

Capabilities

Use Case Fit

Glossary