OpenAI: GPT-5.2
openai/gpt-5.2
GPT-5.2 is the newest frontier-grade model in the GPT-5 family, outperforming GPT-5.1 in agentic capabilities and long-context handling. It uses adaptive reasoning to dynamically allocate compute—responding quickly to straightforward questions while applying deeper analysis to more complex tasks. Designed for broad task coverage, GPT-5.2 delivers consistent improvements across math, coding, science, and tool-calling workloads, producing more coherent long-form responses and more reliable tool use.
by OpenAI
Input type Output type Publish time
2025-12-11
Recent activity on GPT-5.2
Tokens processed per day
Throughput
(tokens/s)
| Providers | Min (tokens/s) | Max (tokens/s) | Avg (tokens/s) |
|---|---|---|---|
| Azure | 9.32 | 22.95 | 14.94 |
| OpenAI | 34.6 | 54.8 | 46.10 |
First Token Latency
(ms)
| Providers | Min (ms) | Max (ms) | Avg (ms) |
|---|---|---|---|
| Azure | 2094 | 4373 | 3177.62 |
| OpenAI | 508 | 7594 | 1615.82 |
Uptime stats for GPT-5.2
Uptime stats for GPT-5.2 across all providers
| Providers | Latency (s) | Throughput (tps) | Uptime (%) |
|---|---|---|---|
| Azure | 4.66 | 4.25 | 100.00 |
Recent uptime
Apr 30, 2026 6:00 PM-
Price
- Input: $ 1.75/ M tokens
- Output: $ 14/ M tokens
- Cache read: $ 0.175/ M tokens
- Web search: $ 0.014/ counts
Model limitation
- Context: 400.00K
- Max output: 128.00K
Supported Parameters
- max_completion_tokens
- temperature
- top_p
- frequency_penalty
- presence_penalty
- seed
- logit_bias
- logprobs
- top_logprobs
- response_format
- stop
- tools
Model Protocol Compatibility
- OpenAI Chat Completions
- OpenAI Responses
- OpenAI Embeddings
- Anthropic Messages
- Google Gemini
- Google Imagen
- Google Video
Sample code and API for GPT-5.2
ZenMux normalizes requests and responses across providers for you.
OpenAI: Python-SDK
from openai import OpenAI
client = OpenAI(
base_url="https://zenmux.ai/api/v1",
api_key="<ZENMUX_API_KEY>",
)
# Chat Completion
completion = client.chat.completions.create(
model="openai/gpt-5.2",
messages=[\
{\
"role": "user",\
"content": "What is the meaning of life?"\
}\
]
)
print(completion.choices[0].message.content)
# Responses API
responses = client.responses.create(
model="openai/gpt-5.2",
input="What is the meaning of life?"
)
print(responses)