hy4-previewTencent
- endpoints
- 1
- regions
- 1
- api
- chat
- released
- August 2026
capabilities 4/8
| # | flags | ||||||
|---|---|---|---|---|---|---|---|
| 1 | Global | 1.0M | $0.83 | $2.50 | $0.04 | zdr |
no measured traffic for this model yet. the endpoints table above carries provider pricing
no published benchmark scores for this model
tencent/hy4-previewthis model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way
Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="tencent/hy4-preview", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models
Hy4 preview is Tencent's flagship class MoE model with 770B total parameters and 49B activated, supporting a 1M token context window. It is optimized for agent, coding, and productivity scenarios, with strong task decomposition, context tracking, instruction following, and long chain execution. It is suited for coding agents, complex tool use, and multi step agentic workflows.
questions 5
Which providers serve hy4-preview?
How much does hy4-preview cost?
Is hy4-preview open weights?
What is the context window of hy4-preview?
How do I use hy4-preview with the OpenAI SDK?
more from tencent 1
| model | context | from /M | providers |
|---|---|---|---|
| hy3 | 262K | $0.13 | 2 |
route hy4-preview through one endpoint
One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology
