Pairwise benchmark snapshot · Aug 16, 2026

DeepSeek R1 vs DeepSeek V3 benchmark

Name: DeepSeek R1 vs DeepSeek V3 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek R1 (DeepSeek) and DeepSeek V3 (DeepSeek) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, DeepSeek R1 is ahead by 48 points (1,358 vs 1,310; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, DeepSeek R1 resolves 65.2% versus 48.6% (seed-bootstrap (Aug 1, 2026)). DeepSeek V3 streams faster (66 tok/s) while DeepSeek V3 is the cheaper output token ($1.03/1M). DeepSeek V3 has the larger context window (164k 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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DeepSeek

DeepSeek R1

Open-weights reasoning model trained with large-scale RL.

Elo 1,358$2.5/1M out

DeepSeek

DeepSeek V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310$1.0287/1M 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.

DeepSeek R1 (4)vsDeepSeek V3 (5)

DeepSeek R1: 4W (44%)Overall: DeepSeek V3DeepSeek V3: 5W (56%)

← DeepSeek R1DeepSeek V3 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,310

Coding Elo

—vs—

SWE-bench

65.2%vs48.6%

LiveBench

59%vs55.4%

GPQA Diamond

79.8%vs59.1%

DeepSeek R1: 4WDeepSeek V3: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs66 tok/s

Time to first token

420 msvs380 ms

DeepSeek R1: 0WDeepSeek V3: 2W

DeepSeek V3 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$1.03/1M

Input price

$0.7/1Mvs$0.26/1M

Context window

64kvs164k

DeepSeek R1: 0WDeepSeek V3: 3W

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 AdvantageEven 3–3

Preference Elo

DeepSeek R1

48 pts advantage

Throughput Speed

DeepSeek V3

4 tok/s faster

Price Efficiency

DeepSeek V3

$1.47/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+4%1,358

EloHigh is better

1,310

LiveBench

High is better

+6%59%

LiveBenchHigh is better

55.4%

SWE-bench

High is better

+34%65.2%

SWE-benchHigh is better

48.6%

GPQA

High is better

+35%79.8%

GPQAHigh is better

59.1%

TTFT

Low is better

420 ms

TTFTLow is better

380 ms+11%

Speed

High is better

62 tok/s

SpeedHigh is better

66 tok/s+6%

In $

Low is better

$0.7/1M

In $Low is better

$0.26/1M+172%

Out $

Low is better

$2.5/1M

Out $Low is better

$1.03/1M+143%

Context

High is better

64k

ContextHigh is better

164k+156%

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 61% with DeepSeek V3

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek R1$62.00 / mo

In: $24.50Out: $37.50

DeepSeek V3$24.44 / mo

In: $9.01Out: $15.43

Estimated Cost Delta

DeepSeek V3 is estimated to save $37.56/month ($451/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek R1:Pick DeepSeek R1 when repo-level coding accuracy is the constraint.
2
DeepSeek V3:Pick DeepSeek V3 when you are optimizing output cost.
3
DeepSeek V3:Pick DeepSeek V3 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek V3

Lower output list price ($1.03/1M).

Voice / low-latency UIDeepSeek V3

Lower TTFT (380 ms).

Long-document RAGDeepSeek V3

Larger window (164k).

Screenshots / visionDeepSeek R1

DeepSeek R1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	DeepSeek V3	Lower output list price ($1.03/1M).
Voice / low-latency UI	DeepSeek V3	Lower TTFT (380 ms).
Long-document RAG	DeepSeek V3	Larger window (164k).
Screenshots / vision	DeepSeek R1	DeepSeek R1 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJan 20, 2025

DeepSeek R1 stays as the open-weights RL baseline

Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.

Community Sentiment

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LIVE

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

DeepSeek

DeepSeek V3

Elo 1,310

LiveBench55.4%

SWE-bench48.6%

Speed66 tok/s

Output cost$1.03/1M

Frequently Asked Questions

Which is better overall, DeepSeek R1 or DeepSeek V3?: DeepSeek R1 has the higher preference Elo in our latest snapshot (1,358). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek R1 or DeepSeek V3?: DeepSeek R1 leads SWE-bench at 65.2% vs 48.6%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek V3 output tokens are $1.03/1M versus $2.5/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek R1 or DeepSeek V3?: DeepSeek V3 has the lower time-to-first-token (380 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: DeepSeek V3 accepts 164k tokens versus 64k.
Can I self-host either model?: Both DeepSeek R1 and DeepSeek V3 are marked open-weights. Hosting cost is not in this table.
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. DeepSeek R1 and DeepSeek V3 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek R1 matchups →|All DeepSeek V3 matchups →

DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V4 Flash vs DeepSeek R1 DeepSeek Coder V2 vs DeepSeek R1 Llama 4 Maverick vs DeepSeek R1 MiniMax M2.5 vs DeepSeek R1

DeepSeek R1 vs DeepSeek V3 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (4)vsDeepSeek V3 (5)

DeepSeek R1: 4W (44%)Overall: DeepSeek V3DeepSeek V3: 5W (56%)

← DeepSeek R1DeepSeek V3 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,310

Coding Elo

—vs—

SWE-bench

65.2%vs48.6%

LiveBench

59%vs55.4%

GPQA Diamond

79.8%vs59.1%

DeepSeek R1: 4WDeepSeek V3: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs66 tok/s

Time to first token

420 msvs380 ms

DeepSeek R1: 0WDeepSeek V3: 2W

DeepSeek V3 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$1.03/1M

Input price

$0.7/1Mvs$0.26/1M

Context window

64kvs164k

DeepSeek R1: 0WDeepSeek V3: 3W

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek V3

Lower output list price ($1.03/1M).

Voice / low-latency UIDeepSeek V3

Lower TTFT (380 ms).

Long-document RAGDeepSeek V3

Larger window (164k).

Screenshots / visionDeepSeek R1

DeepSeek R1 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	DeepSeek V3	Lower output list price ($1.03/1M).
Voice / low-latency UI	DeepSeek V3	Lower TTFT (380 ms).
Long-document RAG	DeepSeek V3	Larger window (164k).
Screenshots / vision	DeepSeek R1	DeepSeek R1 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek R1 or DeepSeek V3?

DeepSeek R1 has the higher preference Elo in our latest snapshot (1,358). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek R1 or DeepSeek V3?

DeepSeek R1 leads SWE-bench at 65.2% vs 48.6%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek V3 output tokens are $1.03/1M versus $2.5/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek R1 or DeepSeek V3?

DeepSeek V3 has the lower time-to-first-token (380 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

DeepSeek V3 accepts 164k tokens versus 64k.

Can I self-host either model?

Both DeepSeek R1 and DeepSeek V3 are marked open-weights. Hosting cost is not in this table.

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. DeepSeek R1 and DeepSeek V3 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

DeepSeek R1

DeepSeek V3

DeepSeek V3

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

DeepSeek R1

DeepSeek V3

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

DeepSeek R1

DeepSeek V3

DeepSeek V3

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

DeepSeek V3

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons