deepseek/deepseek-v3.1-terminus
Ngày phát hành: 2025-09-22
163,840 context · $0.21/M input tokens · $0.79/M output tokens
DeepSeek-V3.1 Terminus is an update to DeepSeek V3.1 that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="deepseek/deepseek-v3.1-terminus",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Model Introduction
Deepseek deepseek-v3.1-terminus
deepseek deepseek-v3.1-terminus
Why It Looks Great
- Large Language Model architecture for efficient processing
- 163840 context window for long document handling
- Competitive pricing at $0.2/$0.9 per million tokens
Key Features
- Context Window: 163840 tokens
- Max Output: 4096 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Deepseek |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 163840 tokens |
| Max Output | 4096 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.2 |
| Output | $0.9 |
How to Use
- Write your prompt — describe the task, provide context, and specify desired output format.
- Submit — the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v3.1-terminus
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="deepseek/deepseek-v3.1-terminus",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "deepseek/deepseek-v3.1-terminus",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: deepseek/deepseek-v3.1-terminus
- Provider: Deepseek
Info
Supported Functionality
API Access Guide
DeepSeek V3.1 Terminus API
deepseek/deepseek-v3.1-terminus
DeepSeek-V3.1 Terminus is an update to DeepSeek V3.1 that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...
Input
$0.21 /M
Output
$0.79 /M
Context
164K
Max Output
4K
Tool Use
Supported
Try DeepSeek V3.1 Terminus on WaveSpeedAI
Access DeepSeek V3.1 Terminus through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about DeepSeek V3.1 Terminus
How much does DeepSeek V3.1 Terminus cost via the API?+
Pricing on WaveSpeedAI: $0.21 per million input tokens and $0.79 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of DeepSeek V3.1 Terminus?+
DeepSeek V3.1 Terminus supports up to 164K tokens of context with up to 4K tokens of output per request.
Is DeepSeek V3.1 Terminus OpenAI-compatible?+
Yes. WaveSpeedAI exposes DeepSeek V3.1 Terminus through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
How do I get started with DeepSeek V3.1 Terminus?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate DeepSeek V3.1 Terminus before paying per token.