GLM-Z1-9B-0414

GLM-Z1-9B-0414 is a 9.4-billion-parameter model from the new GLM-4-0414 series, which came as a genuine surprise even to its developers. Despite its relatively small parameter count, it was trained using all the key techniques employed in creating much larger models within this series. This approach has resulted in unexpectedly high levels of accuracy, logical reasoning, and overall performance.

The model underwent comprehensive training, starting with pre-training on vast volumes of high-quality data, and continuing through advanced post-training stages (preference alignment, rejection sampling, and reinforcement learning based on pairwise ranking feedback). These methods enabled the model to better understand what constitutes the most helpful and accurate responses in specific situations.

Special emphasis was placed on developing reasoning capabilities during training, particularly for solving mathematical problems and logical puzzles. These skills make the model effective not only in standard question-answer scenarios but also in handling more complex analytical tasks. Furthermore, thanks to its compact size, GLM-Z1-9B-0414 demonstrates excellent computational efficiency, making it an ideal choice for resource-constrained environments.

Announce Date: 14.04.2025
Parameters: 9.4B
Context: 32K
Attention Type: Full Attention
VRAM requirements: 5.6 GB using 4 bits quantization
Developer: Z.ai
Transformers Version: 4.52.0.dev0
License: Apache 2.0

Use our pre-built public endpoints to test inference and explore GLM-Z1-9B-0414 capabilities.

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

• maximize endpoint performance,
• enable full context for long sequences,
• ensure top-tier security for data processing in an isolated, dedicated environment,
• use custom weights, such as fine-tuned models or LoRA adapters.

Contact our dedicated neural networks support team at nn@immers.cloud or send your request to the sales department at sale@immers.cloud.