Pairwise benchmark snapshot · Aug 17, 2026

Claude 3.5 Haiku vs DeepSeek V3 benchmark

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

This page compares Claude 3.5 Haiku (Anthropic) and DeepSeek V3 (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, DeepSeek V3 is ahead by 86 points (1,310 vs 1,224; lmarena (Aug 17, 2026)). On SWE-bench coding, DeepSeek V3 resolves 48.6% versus 36.2% (swebench (Aug 17, 2026)). Claude 3.5 Haiku streams faster (140 tok/s) while DeepSeek V3 is the cheaper output token ($1.03/1M). 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 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.

Claude 3.5 Haiku (3)vsDeepSeek V3 (6)

Claude 3.5 Haiku: 3W (33%)Overall: DeepSeek V3DeepSeek V3: 6W (67%)

← Claude 3.5 HaikuDeepSeek V3 →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,224vs1,310

Coding Elo

—vs—

SWE-bench

36.2%vs48.6%

LiveBench

44.8%vs55.4%

GPQA Diamond

54.1%vs59.1%

Claude 3.5 Haiku: 0WDeepSeek V3: 4W

Claude 3.5 Haiku (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

140 tok/svs66 tok/s

Time to first token

110 msvs380 ms

Claude 3.5 Haiku: 2WDeepSeek V3: 0W

DeepSeek V3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4/1Mvs$1.03/1M

Input price

$0.8/1Mvs$0.2574/1M

Context window

200kvs164k

Claude 3.5 Haiku: 1WDeepSeek V3: 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 V3 4/6

Preference Elo

DeepSeek V3

86 pts advantage

Throughput Speed

Claude 3.5 Haiku

74 tok/s faster

Token Price Efficiency

DeepSeek V3

$2.97/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,224

EloHigh is better

1,310+7%

LiveBench

High is better

44.8%

LiveBenchHigh is better

55.4%+24%

SWE-bench

High is better

36.2%

SWE-benchHigh is better

48.6%+34%

GPQA

High is better

54.1%

GPQAHigh is better

59.1%+9%

TTFT

Low is better

+245%110 ms

TTFTLow is better

380 ms

Speed

High is better

+112%140 tok/s

SpeedHigh is better

66 tok/s

In $

Low is better

$0.80 / 1M

In $Low is better

$0.26 / 1M+211%

Out $

Low is better

$4.00 / 1M

Out $Low is better

$1.03 / 1M+289%

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 72% 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)

Claude 3.5 Haiku$88.00 / mo

In: $28Out: $60

DeepSeek V3$24.44 / mo

In: $9.01Out: $15.43

Estimated Cost Delta

DeepSeek V3 is estimated to save $63.56/month ($763/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek V3:Pick DeepSeek V3 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 V3:Pick DeepSeek V3 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsDeepSeek V3

Higher SWE-bench (48.6%).

High-volume chatDeepSeek V3

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

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 V3	Higher SWE-bench (48.6%).
High-volume chat	DeepSeek V3	Lower output list price ($1.03/1M).
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.

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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 V3

Elo 1,310

LiveBench55.4%

SWE-bench48.6%

Speed66 tok/s

Output cost$1.03/1M

Frequently Asked Questions

Which is better overall, Claude 3.5 Haiku or DeepSeek V3?: DeepSeek V3 has the higher preference Elo in our latest snapshot (1,310). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Claude 3.5 Haiku or DeepSeek V3?: DeepSeek V3 leads SWE-bench at 48.6% vs 36.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek V3 output tokens are $1.03/1M versus $4/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.5 Haiku or DeepSeek V3?: Claude 3.5 Haiku has the lower time-to-first-token (110 ms vs 380 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 164k.
Can I self-host either model?: DeepSeek V3 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 V3 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 V3 matchups →

Claude 3.5 Haiku vs Claude Haiku 4.5 (next haiku)DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)Claude Opus 4.5 vs DeepSeek V3 Claude Opus 4.6 vs DeepSeek V3 Claude Sonnet 4.5 vs DeepSeek V3

Claude 3.5 Haiku vs DeepSeek V3 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 V3 (6)

Claude 3.5 Haiku: 3W (33%)Overall: DeepSeek V3DeepSeek V3: 6W (67%)

← Claude 3.5 HaikuDeepSeek V3 →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,224vs1,310

Coding Elo

—vs—

SWE-bench

36.2%vs48.6%

LiveBench

44.8%vs55.4%

GPQA Diamond

54.1%vs59.1%

Claude 3.5 Haiku: 0WDeepSeek V3: 4W

Claude 3.5 Haiku (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

140 tok/svs66 tok/s

Time to first token

110 msvs380 ms

Claude 3.5 Haiku: 2WDeepSeek V3: 0W

DeepSeek V3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4/1Mvs$1.03/1M

Input price

$0.8/1Mvs$0.2574/1M

Context window

200kvs164k

Claude 3.5 Haiku: 1WDeepSeek V3: 2W

Recommended Workload Routing

Repo / coding agentsDeepSeek V3

Higher SWE-bench (48.6%).

High-volume chatDeepSeek V3

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

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 V3	Higher SWE-bench (48.6%).
High-volume chat	DeepSeek V3	Lower output list price ($1.03/1M).
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 V3?

DeepSeek V3 has the higher preference Elo in our latest snapshot (1,310). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude 3.5 Haiku or DeepSeek V3?

DeepSeek V3 leads SWE-bench at 48.6% vs 36.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek V3 output tokens are $1.03/1M versus $4/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Haiku or DeepSeek V3?

Claude 3.5 Haiku has the lower time-to-first-token (110 ms vs 380 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 164k.

Can I self-host either model?

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