gradients-io-tournaments/tournament-llama-test-001-eeb0087a-e949-4294-966b-658ed1f61fee-5CMPlate

TEXT GENERATIONConcurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 6, 2026Architecture:Transformer Featherless Exclusive Cold

The gradients-io-tournaments/tournament-llama-test-001-eeb0087a-e949-4294-966b-658ed1f61fee-5CMPlate model is a 1.5 billion parameter language model with a 32768 token context length. This model is part of a tournament series, indicating its potential use for evaluating and comparing LLM performance in specific tasks. While specific training details are not provided, its participation in a tournament suggests it is designed for competitive evaluation in language understanding and generation tasks.

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Model Overview

This model, gradients-io-tournaments/tournament-llama-test-001-eeb0087a-e949-4294-966b-658ed1f61fee-5CMPlate, is a 1.5 billion parameter language model with a substantial context length of 32768 tokens. It is identified as a participant in a tournament series, implying its primary purpose is for competitive evaluation and benchmarking within specific language model challenges.

Key Characteristics

  • Parameter Count: 1.5 billion parameters, offering a balance between computational efficiency and performance.
  • Context Length: A large 32768 token context window, enabling the processing of extensive inputs and maintaining long-range coherence.
  • Tournament Participation: Designed for evaluation in competitive settings, suggesting a focus on robust performance in defined tasks.

Potential Use Cases

Given its context within a tournament, this model is likely suitable for:

  • Benchmarking: Evaluating performance against other models in specific language understanding or generation tasks.
  • Research & Development: Experimenting with model capabilities under controlled, competitive conditions.
  • Comparative Analysis: Understanding how different model architectures or training methodologies perform on standardized challenges.