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DeepSeek · Open weights

DeepSeek V3.1

Added Jul 26, 2025Open weights

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Use in the app

DeepSeek-V3.1 is a hybrid model that supports both thinking mode and non-thinking mode. It does better at tool calling and agent tasks, and has higher thinking efficiency than its predecessor. This is the non-thinking version. Quantized at FP8.

  • Tools
  • PDF input
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.20
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)
293 tokens
Longer than 30% of 465 models

Side by side

DeepSeek V3.1 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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DeepSeek V3.1DeepSeekThis modelDeepSeek R1 0528DeepSeekRemove
ProviderDeepSeekDeepSeek
Discovery tierOpen weightsOpen weights
AddedJul 26, 2025May 28, 2025
Limits
Context window128K163.84KBest
Max output65.54KBest32.77K
Average output293 tokens1K tokens
Pricing, USD per 1M tokens
Input$0.20Best$0.50
Output$0.70Best$2.15
Cache read—$0.35
Performance
Throughput13.4 tok/s33.0 tok/sBest
Time to first token2.0 s1.3 sBest
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index13.7Best13.1
Math Index49.776.0Best
Capabilities
ReasoningNoYes
ToolsYesYes
PDF inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • DeepSeek V3.1
  • DeepSeek R1 0528

Intelligence Index

  • DeepSeek V3.113.7
  • DeepSeek R1 052813.1

DeepSeek V3.1: Better than 34% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • DeepSeek V3.1: 49.7
    • DeepSeek R1 0528: 76.0Top

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • DeepSeek V3.1: 47.0%
    • DeepSeek R1 0528: 55.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • DeepSeek V3.1: 6.7%
    • DeepSeek R1 0528: 15.8%Top

  • GPQA Diamond

    Graduate-level science questions

    • DeepSeek V3.1: 73.5%
    • DeepSeek R1 0528: 81.3%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • DeepSeek V3.1: 83.3%
    • DeepSeek R1 0528: 84.9%Top

  • IFBench

    Following precise output instructions

    • DeepSeek V3.1: 37.8%
    • DeepSeek R1 0528: 39.6%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • DeepSeek V3.1: 57.7%
    • DeepSeek R1 0528: 77.0%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • DeepSeek V3.1: 49.7%
    • DeepSeek R1 0528: 76.0%Top

  • AIME

    Competition mathematics

    • DeepSeek V3.1: —
    • DeepSeek R1 0528: 89.3%

  • MATH-500

    Competition math problems

    • DeepSeek V3.1: —
    • DeepSeek R1 0528: 98.3%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • DeepSeek V3.1: 24.2%Top
    • DeepSeek R1 0528: 15.9%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • DeepSeek V3.1: 34.8%
    • DeepSeek R1 0528: 36.5%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • DeepSeek V3.1: 47.0%
    • DeepSeek R1 0528: 55.7%Top

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
13.4 tok/s
Faster than 2% of 250 models
Time to first token
2.0 s
Quicker than 80% of 250 models
Prompt cache hits
37.9%
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.

Hourly request success · last 72 hoursLowest hour 96.6%
  • 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.

Read the quickstart
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",
    "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",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

DeepSeek

Other DeepSeek models, starting with the same family.