DeepSeek

DeepSeek V3.1 — Benchmark Scores, Pricing & Performance Analysis

OPEN SOURCEDeepSeek
Chatbot Arena ELO
1340
Output Speed
65 tok/s
Input Cost
$0.25/1M
Output Cost
$0.95/1M
Context Window
164K
Max Output
33K
Knowledge Cutoff
Mar 2025
Accepts
text

DeepSeek V3.1 by DeepSeek demonstrates strong general intelligence, competitive pricing. View detailed benchmark data including scores across coding, math, reasoning, speed, and cost metrics.

Specifications last checked against the provider on . Benchmark scores carry their own source, linked beside each number.

General Benchmarks

Chatbot Arena ELO
134033rd of 74

Human preference ELO from blind head-to-head votes

LMSYS / HuggingFace
MMLU-Pro
78.0%29th of 66

Massive Multitask Language Understanding professional benchmark

HuggingFace Leaderboard
SimpleQA
24.9%10th of 14

Factual accuracy on short, verifiable questions

OpenAI
TruthfulQA
76.5%11th of 13

Resistance to generating false but plausible answers

Papers
MT-Bench
8.88th of 13

Multi-turn conversation quality on 80 curated dialogues

LMSYS
AlpacaEval 2.0
70.0%2nd of 10

Instruction following quality scored by GPT-4 as judge

tatsu-lab

Coding Benchmarks

SWE-bench Verified
46.0%34th of 67

Real-world software engineering task resolution

swebench.com
Website Arena ELO
113574th of 108

Human preference ELO for building a working web page from a brief

Design Arena (via OpenRouter)
LiveCodeBench
48.0%35th of 66

Live competitive programming benchmark

livecodebench.github.io
HumanEval+
84.0%37th of 66

Code generation correctness with extended tests

Papers
Design Arena ELO
113376th of 120

Human preference ELO for building things — websites, UI, games, charts, SVG

Design Arena (via OpenRouter)

Math Benchmarks

GSM8K
92.0%35th of 66

Grade school math word problems

Papers
MATH
82.0%32nd of 66

Competition mathematics problem solving

Papers

Reasoning Benchmarks

τ²-Bench Airline
60.2%67th of 93

Multi-turn service agent making tool calls under strict policy constraints

OpenRouter (measured)
ARC-AGI
35.0%26th of 66

Abstraction and Reasoning Corpus for general intelligence

arcprize.org
GPQA Diamond
79.3%68th of 140

Graduate-level science Q&A by domain experts

Papers
Winogrande
87.5%12th of 14

Commonsense reasoning via pronoun resolution

Papers
BBH
87.5%7th of 13

Big-Bench Hard — 23 challenging multi-step reasoning tasks

Google Research

Speed Benchmarks

Time to First Token
450 ms52nd of 92

Latency before first token arrives

Aggregated
Output Speed
65 tok/s61st of 94

Tokens generated per second

Aggregated

Cost Benchmarks

Output Cost
$0.95194th of 413

Cost per 1M output tokens

OpenRouter API
Input Cost
$0.25188th of 413

Cost per 1M input tokens

OpenRouter API
Cached Input Cost
$0.1374th of 136

Cost per 1M cached input tokens — the price that actually applies to a long agent conversation

OpenRouter API

Context Benchmarks

Context Length
164K208th of 451

Maximum context window size

OpenRouter API

Multimodal Benchmarks

MathVista
68.4%8th of 14

Visual mathematical reasoning across diagrams and charts

Papers

Available from 20 providers

The same model costs different amounts depending on who serves it. You can bring your own key for 8 of these — connect it here.

ProviderInput / 1MOutput / 1MCached inContextYour key
TokenGo$0.19$0.71$0.06131K—
NanoGPT$0.2$0.7$0.1128K—
submodel$0.2$0.8—75K—
Deep Infra$0.25$0.95$0.13164KSupported
OpenRouter$0.25$0.95$0.13164KSupported
Vercel AI Gateway$0.25$0.95$0.13164KSupported
Hugging Face$0.27$1—131KSupported
Jiekou.AI$0.27$1—164K—
Meganova$0.27$1—164K—
NovitaAI$0.27$1$0.135131K—
Baseten$0.5$1.5—164KSupported
Merge Gateway$0.5$1.5—164K—
Abacus$0.55$1.66—128K—
Weights & Biases$0.55$1.65$0.55161K—
Pioneer$0.56$1.68$0.56164K—
Alibaba (China)$0.574$1.721—131K—
Amazon Bedrock$0.58$1.68—164KSupported
Together AI$0.6$1.7—131KSupported
Vertex$0.6$1.7$0.06164KSupported
Qiniu———128K—

DeepSeek V3.1 — Benchmark Scores Overview

Scores normalized to percentage scale for visual comparison. ELO scores mapped to 0-100 range (1100-1500).

DeepSeek V3.1 — Frequently Asked Questions

How intelligent is DeepSeek V3.1?

DeepSeek V3.1 scores 1340 on the Chatbot Arena ELO rating, making it a mid-tier AI model. This score is based on blind head-to-head human preference voting.

How much does DeepSeek V3.1 cost?

DeepSeek V3.1 costs $0.25 per 1M input tokens and $0.95 per 1M output tokens. This makes it one of the more affordable models.

How fast is DeepSeek V3.1?

DeepSeek V3.1 generates output at 65 tokens per second, which is slower, prioritizing quality over speed compared to other models. The time to first token is 450 ms.

How good is DeepSeek V3.1 at coding?

DeepSeek V3.1 achieves 46.0% on SWE-bench Verified, demonstrating moderate real-world software engineering capability. This benchmark tests the model's ability to resolve actual GitHub issues.

How good is DeepSeek V3.1 at math and reasoning?

DeepSeek V3.1 scores 82.0% on the MATH benchmark (competition-level mathematics). It also achieves 79.3% on GPQA Diamond, a graduate-level science reasoning benchmark.

What is the context window of DeepSeek V3.1?

DeepSeek V3.1 has a context window of 164K tokens. This determines how much text, conversation history, and code the model can process in a single request.

Who created DeepSeek V3.1?

DeepSeek V3.1 was created by DeepSeek. It is classified as a open source model in our catalogue.

Is DeepSeek V3.1 open source?

Yes, DeepSeek V3.1 is an open-source model. The model weights are publicly available for download and self-hosting.