DeepSeek · Open weights
DeepSeek V3.1 Terminus
DeepSeek-V3.1-Terminus. The latest update builds on V3.1's strengths while addressing key user feedback. Language consistency improvements (fewer CN/EN mix-ups, no random chars), stronger Code Agent & Search Agent performance, and more stable, reliable outputs across benchmarks. FP8.
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.25
- Output
- $0.70
Reference prices as published by the model provider. API example
Specifications
- Context window
- 128K
- Max output
- 65.5K
- Average output (7 days)
- 364 tokens
- Longer than 37% of 465 models
Side by side
Compare models
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Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
Intelligence Index
13.9
Better than 34% of 326 scored models
Indexes
Math Index
53.7Composite of the math evaluations
Better than 49% of 118 scored models
Document reasoning
AA-LCRv1.1
45.3%Reasoning across long documents
Better than 22% of 309 scored models
Reasoning and knowledge
Humanity’s Last Exam
8.7%Expert-level questions across academic fields
Better than 29% of 323 scored models
GPQA Diamond
75.1%Graduate-level science questions
Better than 36% of 291 scored models
MMLU-Pro
83.6%Multi-subject knowledge and reasoning
Better than 76% of 132 scored models
IFBench
41.2%Following precise output instructions
Better than 30% of 215 scored models
Coding
LiveCodeBench
52.9%Recent competitive programming problems
Better than 45% of 129 scored models
Math
AIME 2025
53.7%Competition mathematics, 2025 problems
Better than 49% of 118 scored models
Legacy evaluations
Terminal-Bench Hard
31.8%Earlier terminal task suite
Better than 58% of 212 scored models
τ²-Bench Telecom
37.1%Tool use in a customer-support simulation
Better than 31% of 214 scored models
AA-LCR (unversioned)
45.3%Long-context reasoning, earlier grading
Better than 22% of 309 scored models
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 21.1 tok/s
- Faster than 10% of 247 models
- Time to first token
- 2.9 s
- Quicker than 60% of 247 models
- Prompt cache hits
- 72.8%
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-ai/DeepSeek-V3.1-Terminus",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V3.1-Terminus",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)DeepSeek
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