GLM-Z1-9B-0414

reasoning

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: 10B
Context: 33K
Layers: 40
Attention Type: Full Attention
Developer: Z.ai
Transformers Version: 4.52.0.dev0
License: Apache 2.0

Public endpoint

Use our pre-built public endpoints for free to test inference and explore GLM-Z1-9B-0414 capabilities. You can obtain an API access token on the token management page after registration and verification.
Model Name Context Type GPU Status Link
There are no public endpoints for this model yet.

Private server

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.

Recommended server configurations for hosting GLM-Z1-9B-0414

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-1.16.32.160
32,768.0
1 $0.38 14.84 3.306 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 43.50 9.120 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 78.14 9.900 Launch
rtx3080-2.16.32.160
32,768.0
tensor
2 $0.97 73.98 5.730 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 109.82 9.871 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 25.128 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 15.634 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 71.57 50.768 Launch
h100-1.16.64.160
32,768.0
1 $3.83 107.92 49.996 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 61.074 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 107.104 Launch
h200-1.16.128.160
32,768.0
1 $4.74 95.453 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 196.234 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-1.16.32.160
32,768.0
1 $0.53 1.765 Launch
teslaa2-2.16.32.160
32,768.0
tensor
2 $0.57 5.950 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 43.15 1.772 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 2.516 Launch
rtx3080-3.16.64.160
32,768.0
pipeline
3 $1.43 33.56 4.043 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 19.139 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 8.279 Launch
rtx3080-4.16.64.160
32,768.0
tensor
4 $1.82 5.629 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 48.25 42.936 Launch
h100-1.16.64.160
32,768.0
1 $3.83 43.482 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 53.720 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 101.115 Launch
h200-1.16.128.160
32,768.0
1 $4.74 88.098 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 190.244 Launch

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