Using GLM-5 on Together AI

Implementation guide · GLM-5 · Zhipu AI

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Together AI exposes GLM-5 through model ID glm-5. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-30. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Together AI and generate an API key.
  2. 2
    Use the Together AI SDK or REST API to call glm-5 — see the documentation for request format.
  3. 3
    You'll be billed $1.00/1M input, $3.20/1M output tokens. See full pricing.

Code Examples

Install
pip install together
API key
TOGETHER_API_KEY
Model ID
glm-5

Together uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.

from together import Together

client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="glm-5",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Together AI

TypePrice (per 1M)
Input tokens$1.00
Output tokens$3.20

Capabilities

ReasoningJSON / Tool useStructured OutputsPrompt Caching

About GLM-5

Flagship open-weight foundation model from Zhipu AI with 744B parameters (40B active per token) in Mixture of Experts architecture. Trained on 28.5T tokens using DeepSeek Sparse Attention on Huawei Ascend hardware. Achieves state-of-the-art performance on coding and agentic benchmarks (SWE-bench Verified: 77.8%). Supports autonomous planning, multi-step tool use, and self-correction.

Model Specs

Released2026-02-11
Parameters744B total, 40B active
Context200k
ArchitectureMixture of Experts
Knowledge cutoff2025-11

Provider

Together AI

San Francisco, California, United States