GLM-4-32B-0414

GLM-4-32B-Base-0414 is a base model with 32 billion parameters from the new GLM-4–0414 series developed by Team GLM. It was trained on 15TB of high-quality data, including a significant amount of synthetic materials focused on logical reasoning. This training enables a solid foundation for subsequent reinforcement learning and adaptation to user preferences.

The model was developed under the "all tools" concept, allowing it to efficiently interact with external resources such as Python, web search, user APIs, and other services. Thanks to this capability, it demonstrates excellent performance in handling complex agent-like tasks, including code generation, function calling, information retrieval, and report creation.

Its performance is comparable to industry leaders like GPT-4o and DeepSeek-V3-0324 (671B), especially in programming tasks. The model is capable of generating over 500 lines of functional code in various programming languages without additional prompts. It supports a context length of up to 128K tokens (using YaRN, with a base of 32K) and offers convenient local deployment, making it a versatile solution for enterprise applications where result predictability and stability are critical.


Announce Date: 14.04.2025
Parameters: 32B
Context: 33K
Layers: 61
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-4-32B-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

API access to GLM-4-32B-0414 endpoints

There are no public endpoints for this model yet.

Private endpoint

An endpoint is a server with pre-installed software that automatically downloads neural network weights and launches an OpenAI-compatible API to handle incoming requests.

A private endpoint is created within the user's project, belongs exclusively to the user, and is billed per server configuration in accordance with the infrastructure pricing.

We recommend creating private endpoints when you need to:

  • achieve maximum endpoint performance,
  • access the full context window for processing large requests and conversations,
  • ensure maximum security by processing data in a dedicated, isolated environment.

Recommended server configurations for creating a private inference endpoint GLM-4-32B-0414

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-2.16.64.160
32,768.0
tensor
2 $0.93 8.336 Launch
teslaa2-3.32.128.160
32,768.0
pipeline
3 $1.06 5.842 Launch
teslaa2-4.32.128.160
32,768.0
tensor
4 $1.26 6.027 Launch
rtx3090-2.16.64.160
32,768.0
tensor
2 $1.56 57.97 9.359 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 9.359 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 3.122 Launch
rtx3080-4.16.64.160
32,768.0
tensor
4 $1.82 1.210 Launch
rtx4090-2.16.64.160
32,768.0
tensor
2 $1.92 68.06 9.320 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 58.83 26.240 Launch
h100-1.16.64.160
32,768.0
1 $3.83 54.91 26.206 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 32.920 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 63.113 Launch
h200-1.16.128.160
32,768.0
1 $4.74 55.463 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 121.559 Launch

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

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