Pairwise benchmark snapshot · Aug 17, 2026

Claude 3.5 Haiku vs DeepSeek R1 benchmark

Name: Claude 3.5 Haiku vs DeepSeek R1 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3.5 Haiku (Anthropic) and DeepSeek R1 (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, DeepSeek R1 is ahead by 134 points (1,358 vs 1,224; lmarena (Aug 17, 2026)). On SWE-bench coding, DeepSeek R1 resolves 65.2% versus 36.2% (swebench (Aug 17, 2026)). Claude 3.5 Haiku streams faster (140 tok/s) while DeepSeek R1 is the cheaper output token ($2.5/1M). Claude 3.5 Haiku 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 Haiku

Previous cheap Claude. Haiku 4.5 is the current $1/$5 SKU.

Elo 1,224$4/1M out

DeepSeek

DeepSeek R1

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

Elo 1,358$2.5/1M 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 Haiku (3)vsDeepSeek R1 (6)

Claude 3.5 Haiku: 3W (33%)Overall: DeepSeek R1DeepSeek R1: 6W (67%)

← Claude 3.5 HaikuDeepSeek R1 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,224vs1,358

Coding Elo

—vs—

SWE-bench

36.2%vs65.2%

LiveBench

44.8%vs59%

GPQA Diamond

54.1%vs79.8%

Claude 3.5 Haiku: 0WDeepSeek R1: 4W

Claude 3.5 Haiku (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

140 tok/svs62 tok/s

Time to first token

110 msvs420 ms

Claude 3.5 Haiku: 2WDeepSeek R1: 0W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4/1Mvs$2.5/1M

Input price

$0.8/1Mvs$0.7/1M

Context window

200kvs64k

Claude 3.5 Haiku: 1WDeepSeek R1: 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 AdvantageDeepSeek R1 4/6

Preference Elo

DeepSeek R1

134 pts advantage

Throughput Speed

Claude 3.5 Haiku

78 tok/s faster

Price Efficiency

DeepSeek R1

$1.50/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,224

EloHigh is better

1,358+11%

LiveBench

High is better

44.8%

LiveBenchHigh is better

59%+32%

SWE-bench

High is better

36.2%

SWE-benchHigh is better

65.2%+80%

GPQA

High is better

54.1%

GPQAHigh is better

79.8%+48%

TTFT

Low is better

+282%110 ms

TTFTLow is better

420 ms

Speed

High is better

+126%140 tok/s

SpeedHigh is better

62 tok/s

In $

Low is better

$0.8/1M

In $Low is better

$0.7/1M+14%

Out $

Low is better

$4/1M

Out $Low is better

$2.5/1M+60%

Context

High is better

+213%200k

ContextHigh is better

64k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 30% with DeepSeek R1

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 Haiku$88.00 / mo

In: $28.00Out: $60.00

DeepSeek R1$62.00 / mo

In: $24.50Out: $37.50

Estimated Cost Delta

DeepSeek R1 is estimated to save $26.00/month ($312/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
Claude 3.5 Haiku:Pick Claude 3.5 Haiku when time-to-first-token matters more than peak Elo.
3
DeepSeek R1:Pick DeepSeek R1 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek R1

Lower output list price ($2.5/1M).

Voice / low-latency UIClaude 3.5 Haiku

Lower TTFT (110 ms).

Long-document RAGClaude 3.5 Haiku

Larger window (200k).

Screenshots / visionClaude 3.5 Haiku

Claude 3.5 Haiku 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 R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Claude 3.5 Haiku	Lower TTFT (110 ms).
Long-document RAG	Claude 3.5 Haiku	Larger window (200k).
Screenshots / vision	Claude 3.5 Haiku	Claude 3.5 Haiku 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

Anthropic

Claude 3.5 Haiku

Elo 1,224

LiveBench44.8%

SWE-bench36.2%

Speed140 tok/s

Output cost$4/1M

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

Frequently Asked Questions

Which is better overall, Claude 3.5 Haiku or DeepSeek R1?: 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, Claude 3.5 Haiku or DeepSeek R1?: DeepSeek R1 leads SWE-bench at 65.2% vs 36.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek R1 output tokens are $2.5/1M versus $4/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.5 Haiku or DeepSeek R1?: Claude 3.5 Haiku has the lower time-to-first-token (110 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Claude 3.5 Haiku accepts 200k tokens versus 64k.
Can I self-host either model?: DeepSeek R1 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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 Haiku and DeepSeek R1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude 3.5 Haiku matchups →|All DeepSeek R1 matchups →

Claude 3.5 Haiku vs Claude Haiku 4.5 (next haiku)DeepSeek R1 vs DeepSeek V3 (previous deepseek)DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)Claude Opus 4.5 vs DeepSeek R1 Claude Opus 4.6 vs DeepSeek R1 Claude Sonnet 4.5 vs DeepSeek R1

Claude 3.5 Haiku vs DeepSeek R1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.5 Haiku (3)vsDeepSeek R1 (6)

Claude 3.5 Haiku: 3W (33%)Overall: DeepSeek R1DeepSeek R1: 6W (67%)

← Claude 3.5 HaikuDeepSeek R1 →

DeepSeek R1 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,224vs1,358

Coding Elo

—vs—

SWE-bench

36.2%vs65.2%

LiveBench

44.8%vs59%

GPQA Diamond

54.1%vs79.8%

Claude 3.5 Haiku: 0WDeepSeek R1: 4W

Claude 3.5 Haiku (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

140 tok/svs62 tok/s

Time to first token

110 msvs420 ms

Claude 3.5 Haiku: 2WDeepSeek R1: 0W

DeepSeek R1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4/1Mvs$2.5/1M

Input price

$0.8/1Mvs$0.7/1M

Context window

200kvs64k

Claude 3.5 Haiku: 1WDeepSeek R1: 2W

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatDeepSeek R1

Lower output list price ($2.5/1M).

Voice / low-latency UIClaude 3.5 Haiku

Lower TTFT (110 ms).

Long-document RAGClaude 3.5 Haiku

Larger window (200k).

Screenshots / visionClaude 3.5 Haiku

Claude 3.5 Haiku 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 R1	Lower output list price ($2.5/1M).
Voice / low-latency UI	Claude 3.5 Haiku	Lower TTFT (110 ms).
Long-document RAG	Claude 3.5 Haiku	Larger window (200k).
Screenshots / vision	Claude 3.5 Haiku	Claude 3.5 Haiku is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude 3.5 Haiku or DeepSeek R1?

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, Claude 3.5 Haiku or DeepSeek R1?

DeepSeek R1 leads SWE-bench at 65.2% vs 36.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek R1 output tokens are $2.5/1M versus $4/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Haiku or DeepSeek R1?

Claude 3.5 Haiku has the lower time-to-first-token (110 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Claude 3.5 Haiku accepts 200k tokens versus 64k.

Can I self-host either model?

DeepSeek R1 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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 Haiku and DeepSeek R1 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

Claude 3.5 Haiku

DeepSeek R1

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

Claude 3.5 Haiku

DeepSeek R1

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

Claude 3.5 Haiku

DeepSeek R1

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

Claude 3.5 Haiku

DeepSeek R1

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons