Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Claude 3.5 Sonnet vs DeepSeek: DeepSeek V3.1 benchmark

Name: Claude 3.5 Sonnet vs DeepSeek: DeepSeek V3.1 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3.5 Sonnet (Anthropic) and DeepSeek: DeepSeek V3.1 (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. DeepSeek: DeepSeek V3.1 wins on output price at $0.95/1M. Claude 3.5 Sonnet has the larger context window (200k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Anthropic

Claude 3.5 Sonnet

2024 workhorse. Still a high-intent compare against GPT-4o.

Elo 1,280$15/1M out

DeepSeek

DeepSeek: DeepSeek V3.1

Auto-discovered from OpenRouter (deepseek/deepseek-chat-v3.1). Preview until a second source matches.

$0.95/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.5 Sonnet (7)vsDeepSeek: DeepSeek V3.1 (2)

Claude 3.5 Sonnet: 7W (78%)Overall: Claude 3.5 SonnetDeepSeek: DeepSeek V3.1: 2W (22%)

← Claude 3.5 SonnetDeepSeek: DeepSeek V3.1 →

Claude 3.5 Sonnet (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,280vs—

Coding Elo

—vs—

SWE-bench

49%vs—

LiveBench

52.1%vs—

GPQA Diamond

65%vs—

Claude 3.5 Sonnet: 4WDeepSeek: DeepSeek V3.1: 0W

Claude 3.5 Sonnet (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

80 tok/svs—

Time to first token

280 msvs—

Claude 3.5 Sonnet: 2WDeepSeek: DeepSeek V3.1: 0W

DeepSeek: DeepSeek V3.1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$0.95/1M

Input price

$3/1Mvs$0.25/1M

Context window

200kvs164k

Claude 3.5 Sonnet: 1WDeepSeek: DeepSeek V3.1: 2W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageClaude 3.5 Sonnet 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

DeepSeek: DeepSeek V3.1

$14.05/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,280

EloHigh is better

—

LiveBench

High is better

52.1%

LiveBenchHigh is better

—

SWE-bench

High is better

49%

SWE-benchHigh is better

—

GPQA

High is better

65%

GPQAHigh is better

—

TTFT

Low is better

280 ms

TTFTLow is better

—

Speed

High is better

80 tok/s

SpeedHigh is better

—

In $

Low is better

$3.00 / 1M

In $Low is better

$0.25 / 1M+1100%

Out $

Low is better

$15.00 / 1M

Out $Low is better

$0.95 / 1M+1479%

Context

High is better

+22%200k

ContextHigh is better

164k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 93% with DeepSeek: DeepSeek V3.1

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Claude 3.5 Sonnet$330.00 / mo

In: $105Out: $225

DeepSeek: DeepSeek V3.1$23.00 / mo

In: $8.75Out: $14.25

Estimated Cost Delta

DeepSeek: DeepSeek V3.1 is estimated to save $307.00/month ($3,684/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek: DeepSeek V3.1:Pick DeepSeek: DeepSeek V3.1 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.1

Lower output list price ($0.95/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude 3.5 Sonnet

Larger window (200k).

Screenshots / visionClaude 3.5 Sonnet

Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	DeepSeek: DeepSeek V3.1	Lower output list price ($0.95/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude 3.5 Sonnet	Larger window (200k).
Screenshots / vision	Claude 3.5 Sonnet	Claude 3.5 Sonnet is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

Anthropic

Claude 3.5 Sonnet

Elo 1,280

LiveBench52.1%

SWE-bench49%

Speed80 tok/s

Output cost$15/1M

DeepSeek

DeepSeek: DeepSeek V3.1

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.95/1M

Frequently Asked Questions

Which is better overall, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: DeepSeek: DeepSeek V3.1 output tokens are $0.95/1M versus $15/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?: We do not have TTFT for both models.
Which has the larger context window?: Claude 3.5 Sonnet accepts 200k tokens versus 164k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Claude 3.5 Sonnet and DeepSeek: DeepSeek V3.1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude 3.5 Sonnet matchups →|All DeepSeek: DeepSeek V3.1 matchups →

Claude 3.5 Sonnet vs Claude 3.7 Sonnet (next sonnet)Claude Opus 4.5 vs Claude 3.5 Sonnet Claude Opus 4.6 vs Claude 3.5 Sonnet Claude Sonnet 4.5 vs Claude 3.5 Sonnet Claude Opus 5 vs Claude 3.5 Sonnet Claude Fable 5 vs Claude 3.5 Sonnet

Claude 3.5 Sonnet vs DeepSeek: DeepSeek V3.1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.5 Sonnet (7)vsDeepSeek: DeepSeek V3.1 (2)

Claude 3.5 Sonnet: 7W (78%)Overall: Claude 3.5 SonnetDeepSeek: DeepSeek V3.1: 2W (22%)

← Claude 3.5 SonnetDeepSeek: DeepSeek V3.1 →

Claude 3.5 Sonnet (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,280vs—

Coding Elo

—vs—

SWE-bench

49%vs—

LiveBench

52.1%vs—

GPQA Diamond

65%vs—

Claude 3.5 Sonnet: 4WDeepSeek: DeepSeek V3.1: 0W

Claude 3.5 Sonnet (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

80 tok/svs—

Time to first token

280 msvs—

Claude 3.5 Sonnet: 2WDeepSeek: DeepSeek V3.1: 0W

DeepSeek: DeepSeek V3.1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$0.95/1M

Input price

$3/1Mvs$0.25/1M

Context window

200kvs164k

Claude 3.5 Sonnet: 1WDeepSeek: DeepSeek V3.1: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.1

Lower output list price ($0.95/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude 3.5 Sonnet

Larger window (200k).

Screenshots / visionClaude 3.5 Sonnet

Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	DeepSeek: DeepSeek V3.1	Lower output list price ($0.95/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude 3.5 Sonnet	Larger window (200k).
Screenshots / vision	Claude 3.5 Sonnet	Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

DeepSeek: DeepSeek V3.1 output tokens are $0.95/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Sonnet or DeepSeek: DeepSeek V3.1?

We do not have TTFT for both models.

Which has the larger context window?

Claude 3.5 Sonnet accepts 200k tokens versus 164k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Claude 3.5 Sonnet and DeepSeek: DeepSeek V3.1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.