Last refreshed 2026-06-30. Next refresh: weekly.
Why use GLM-5 on Together AI?
Together AI offers GLM-5 with pay-as-you-go pricing at $1.00/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Compare GLM-5 across 7 providers to find the best fit for your use caseInput / 1M
$1.00
Output / 1M
$3.20
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install togetherAuth
export TOGETHER_API_KEY=...Call
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="glm-5",Model ID
glm-5Request example
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)Gotchas
- 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.
- The examples expect TOGETHER_API_KEY; rename it only if your application config maps the new variable.
Compare GLM-5 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Fireworks AI | $1.00 | $3.20 |
| OpenRouter | $0.60 | $2.08 |
| Together AI | $1.00 | $3.20 |
| GCP Vertex AI | $1.00 | $3.20 |
| NVIDIA NIM | — | — |
Pricing
| Type | Price (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.
Get Started
Model Specs
Released2026-02-11
Parameters744B total, 40B active
Context200k
ArchitectureMixture of Experts
Knowledge cutoff2025-11