Pairwise benchmark snapshot · Aug 17, 2026

Claude 3.5 Sonnet vs OpenAI o1-mini benchmark

Name: Claude 3.5 Sonnet vs OpenAI o1-mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3.5 Sonnet (Anthropic) and OpenAI o1-mini (OpenAI) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, OpenAI o1-mini is ahead by 165 points (1,445 vs 1,280; lmarena (Aug 17, 2026)). On SWE-bench coding, OpenAI o1-mini resolves 56.4% versus 49% (swebench (Aug 17, 2026)). OpenAI o1-mini streams faster (85 tok/s) while OpenAI o1-mini is the cheaper output token ($4.4/1M). 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

OpenAI

OpenAI o1-mini

OpenAI high-speed, cost-effective reasoning model optimized for STEM, math, and code generation.

Elo 1,445$4.4/1M 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 (1)vsOpenAI o1-mini (8)

Claude 3.5 Sonnet: 1W (11%)Overall: OpenAI o1-miniOpenAI o1-mini: 8W (89%)

← Claude 3.5 Sonnet1 tiesOpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,280vs1,445

Coding Elo

—vs1,468

SWE-bench

49%vs56.4%

LiveBench

52.1%vs62%

GPQA Diamond

65%vs76.8%

Claude 3.5 Sonnet: 0WOpenAI o1-mini: 5W

OpenAI o1-mini (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

80 tok/svs85 tok/s

Time to first token

280 msvs280 ms

Claude 3.5 Sonnet: 0WOpenAI o1-mini: 1W

OpenAI o1-mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$4.4/1M

Input price

$3/1Mvs$1.1/1M

Context window

200kvs128k

Claude 3.5 Sonnet: 1WOpenAI o1-mini: 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 AdvantageOpenAI o1-mini 5/6

Preference Elo

OpenAI o1-mini

165 pts advantage

Throughput Speed

OpenAI o1-mini

5 tok/s faster

Token Price Efficiency

OpenAI o1-mini

$10.60/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,280

EloHigh is better

1,445+13%

Code Elo

High is better

—

Code EloHigh is better

1,468

LiveBench

High is better

52.1%

LiveBenchHigh is better

62%+19%

SWE-bench

High is better

49%

SWE-benchHigh is better

56.4%+15%

GPQA

High is better

65%

GPQAHigh is better

76.8%+18%

TTFT

Low is better

280 ms

TTFTLow is better

280 ms

Speed

High is better

80 tok/s

SpeedHigh is better

85 tok/s+6%

In $

Low is better

$3.00 / 1M

In $Low is better

$1.10 / 1M+173%

Out $

Low is better

$15.00 / 1M

Out $Low is better

$4.40 / 1M+241%

Context

High is better

+56%200k

ContextHigh is better

128k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 68% with OpenAI o1-mini

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

OpenAI o1-mini$104.50 / mo

In: $38.5Out: $66

Estimated Cost Delta

OpenAI o1-mini is estimated to save $225.50/month ($2,706/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI o1-mini:Pick OpenAI o1-mini when repo-level coding accuracy is the constraint.
2
Claude 3.5 Sonnet:Pick Claude 3.5 Sonnet when time-to-first-token matters more than peak Elo.
3
OpenAI o1-mini:Pick OpenAI o1-mini as the default general assistant.

Recommended Workload Routing

Repo / coding agentsOpenAI o1-mini

Higher SWE-bench (56.4%).

High-volume chatOpenAI o1-mini

Lower output list price ($4.4/1M).

Voice / low-latency UIClaude 3.5 Sonnet

Lower TTFT (280 ms).

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	OpenAI o1-mini	Higher SWE-bench (56.4%).
High-volume chat	OpenAI o1-mini	Lower output list price ($4.4/1M).
Voice / low-latency UI	Claude 3.5 Sonnet	Lower TTFT (280 ms).
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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LIVE

Anthropic

Claude 3.5 Sonnet

Elo 1,280

LiveBench52.1%

SWE-bench49%

Speed80 tok/s

Output cost$15/1M

OpenAI

OpenAI o1-mini

Elo 1,445

LiveBench62%

SWE-bench56.4%

Speed85 tok/s

Output cost$4.4/1M

Frequently Asked Questions

Which is better overall, Claude 3.5 Sonnet or OpenAI o1-mini?: OpenAI o1-mini has the higher preference Elo in our latest snapshot (1,445). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Claude 3.5 Sonnet or OpenAI o1-mini?: OpenAI o1-mini leads SWE-bench at 56.4% vs 49%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: OpenAI o1-mini output tokens are $4.4/1M versus $15/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.5 Sonnet or OpenAI o1-mini?: Claude 3.5 Sonnet has the lower time-to-first-token (280 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Claude 3.5 Sonnet accepts 200k tokens versus 128k.
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 OpenAI o1-mini 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 OpenAI o1-mini matchups →

Claude 3.5 Sonnet vs Claude 3.7 Sonnet (next sonnet)OpenAI o1-mini vs GPT-4o mini (previous gpt-mini)OpenAI o1-mini vs OpenAI: o3 Mini (next gpt-mini)Claude Opus 4.5 vs OpenAI o1-mini Claude Opus 4.6 vs OpenAI o1-mini Claude Sonnet 4.5 vs OpenAI o1-mini

Claude 3.5 Sonnet vs OpenAI o1-mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.5 Sonnet (1)vsOpenAI o1-mini (8)

Claude 3.5 Sonnet: 1W (11%)Overall: OpenAI o1-miniOpenAI o1-mini: 8W (89%)

← Claude 3.5 Sonnet1 tiesOpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,280vs1,445

Coding Elo

—vs1,468

SWE-bench

49%vs56.4%

LiveBench

52.1%vs62%

GPQA Diamond

65%vs76.8%

Claude 3.5 Sonnet: 0WOpenAI o1-mini: 5W

OpenAI o1-mini (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

80 tok/svs85 tok/s

Time to first token

280 msvs280 ms

Claude 3.5 Sonnet: 0WOpenAI o1-mini: 1W

OpenAI o1-mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$4.4/1M

Input price

$3/1Mvs$1.1/1M

Context window

200kvs128k

Claude 3.5 Sonnet: 1WOpenAI o1-mini: 2W

Recommended Workload Routing

Repo / coding agentsOpenAI o1-mini

Higher SWE-bench (56.4%).

High-volume chatOpenAI o1-mini

Lower output list price ($4.4/1M).

Voice / low-latency UIClaude 3.5 Sonnet

Lower TTFT (280 ms).

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	OpenAI o1-mini	Higher SWE-bench (56.4%).
High-volume chat	OpenAI o1-mini	Lower output list price ($4.4/1M).
Voice / low-latency UI	Claude 3.5 Sonnet	Lower TTFT (280 ms).
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 OpenAI o1-mini?

OpenAI o1-mini has the higher preference Elo in our latest snapshot (1,445). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude 3.5 Sonnet or OpenAI o1-mini?

OpenAI o1-mini leads SWE-bench at 56.4% vs 49%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

OpenAI o1-mini output tokens are $4.4/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Sonnet or OpenAI o1-mini?

Claude 3.5 Sonnet has the lower time-to-first-token (280 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Claude 3.5 Sonnet accepts 200k tokens versus 128k.

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 OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.