Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

Claude Opus 4.6 vs OpenAI: o1 (batch) benchmark

Name: Claude Opus 4.6 vs OpenAI: o1 (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude Opus 4.6 (Anthropic) and OpenAI: o1 (batch) (OpenAI) using the latest snapshots we have as of Aug 16, 2026. Claude Opus 4.6 wins on output price at $25/1M. Claude Opus 4.6 has the larger context window (1M 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 Opus 4.6

Follow-on Opus release. Slightly behind 4.5 on official SWE-bench bash-only in the last published sweep; stronger long-horizon agent traces.

Elo 1,574$25/1M out

OpenAI

OpenAI: o1 (batch)

Auto-discovered from OpenRouter (openai/o1:batch). Preview until a second source matches.

$30/1M out

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Quick vs:vs Claude Opus 4.5 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet vs GPT-5

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (10)vsOpenAI: o1 (batch) (0)

Claude Opus 4.6: 10W (100%)Overall: Claude Opus 4.6OpenAI: o1 (batch): 0W (0%)

← Claude Opus 4.6OpenAI: o1 (batch) →

Claude Opus 4.6 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,574vs—

Coding Elo

1,570vs—

SWE-bench

75.9%vs—

LiveBench

72%vs—

GPQA Diamond

84.8%vs—

Claude Opus 4.6: 5WOpenAI: o1 (batch): 0W

Claude Opus 4.6 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

64 tok/svs—

Time to first token

360 msvs—

Claude Opus 4.6: 2WOpenAI: o1 (batch): 0W

Claude Opus 4.6 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$30/1M

Input price

$5/1Mvs$7.5/1M

Context window

1Mvs200k

Claude Opus 4.6: 3WOpenAI: o1 (batch): 0W

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 Opus 4.6 6/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Claude Opus 4.6

$5.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,574

EloHigh is better

—

Code Elo

High is better

1,570

Code EloHigh is better

—

LiveBench

High is better

72%

LiveBenchHigh is better

—

SWE-bench

High is better

75.9%

SWE-benchHigh is better

—

GPQA

High is better

84.8%

GPQAHigh is better

—

TTFT

Low is better

360 ms

TTFTLow is better

—

Speed

High is better

64 tok/s

SpeedHigh is better

—

In $

Low is better

+50%$5/1M

In $Low is better

$7.5/1M

Out $

Low is better

+20%$25/1M

Out $Low is better

$30/1M

Context

High is better

+400%1M

ContextHigh is better

200k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 23% with Claude Opus 4.6

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Claude Opus 4.6$550.00 / mo

In: $175.00Out: $375.00

OpenAI: o1 (batch)$712.50 / mo

In: $262.50Out: $450.00

Estimated Cost Delta

Claude Opus 4.6 is estimated to save $162.50/month ($1,950/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Claude Opus 4.6:Pick Claude Opus 4.6 when you are optimizing output cost.
2
Claude Opus 4.6:Pick Claude Opus 4.6 for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatClaude Opus 4.6

Lower output list price ($25/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude Opus 4.6

Larger window (1M).

Screenshots / visionClaude Opus 4.6

Claude Opus 4.6 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	Claude Opus 4.6	Lower output list price ($25/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude Opus 4.6	Larger window (1M).
Screenshots / vision	Claude Opus 4.6	Claude Opus 4.6 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchMay 10, 2026

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Slightly behind 4.5 on one official SWE-bench sweep; stronger long-horizon traces. We keep the row for old vs URLs.

Community Sentiment

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LIVE

Anthropic

Claude Opus 4.6

Elo 1,574

LiveBench72%

SWE-bench75.9%

Speed64 tok/s

Output cost$25/1M

OpenAI

OpenAI: o1 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$30/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or OpenAI: o1 (batch)?: 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 Opus 4.6 or OpenAI: o1 (batch)?: 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?: Claude Opus 4.6 output tokens are $25/1M versus $30/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4.6 or OpenAI: o1 (batch)?: We do not have TTFT for both models.
Which has the larger context window?: Claude Opus 4.6 accepts 1M tokens versus 200k.
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 Opus 4.6 and OpenAI: o1 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude Opus 4.6 matchups →|All OpenAI: o1 (batch) matchups →

Claude Opus 4.6 vs Claude Opus 4.5 (previous opus)Claude Opus 4.6 vs Claude Opus 4.8 (next opus)GPT-5 vs Claude Opus 4.6 Claude Sonnet 5 vs Claude Opus 4.6 GPT-5.6 Terra vs Claude Opus 4.6 GPT-4.5 Orion vs Claude Opus 4.6

Claude Opus 4.6 vs OpenAI: o1 (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (10)vsOpenAI: o1 (batch) (0)

Claude Opus 4.6: 10W (100%)Overall: Claude Opus 4.6OpenAI: o1 (batch): 0W (0%)

← Claude Opus 4.6OpenAI: o1 (batch) →

Claude Opus 4.6 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,574vs—

Coding Elo

1,570vs—

SWE-bench

75.9%vs—

LiveBench

72%vs—

GPQA Diamond

84.8%vs—

Claude Opus 4.6: 5WOpenAI: o1 (batch): 0W

Claude Opus 4.6 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

64 tok/svs—

Time to first token

360 msvs—

Claude Opus 4.6: 2WOpenAI: o1 (batch): 0W

Claude Opus 4.6 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$30/1M

Input price

$5/1Mvs$7.5/1M

Context window

1Mvs200k

Claude Opus 4.6: 3WOpenAI: o1 (batch): 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatClaude Opus 4.6

Lower output list price ($25/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude Opus 4.6

Larger window (1M).

Screenshots / visionClaude Opus 4.6

Claude Opus 4.6 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	Claude Opus 4.6	Lower output list price ($25/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude Opus 4.6	Larger window (1M).
Screenshots / vision	Claude Opus 4.6	Claude Opus 4.6 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or OpenAI: o1 (batch)?

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 Opus 4.6 or OpenAI: o1 (batch)?

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?

Claude Opus 4.6 output tokens are $25/1M versus $30/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude Opus 4.6 or OpenAI: o1 (batch)?

We do not have TTFT for both models.

Which has the larger context window?

Claude Opus 4.6 accepts 1M tokens versus 200k.

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 Opus 4.6 and OpenAI: o1 (batch) 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

No shared data

No shared data

Claude Opus 4.6

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Claude Opus 4.6

OpenAI: o1 (batch)

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

No shared data

No shared data

Claude Opus 4.6

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Claude Opus 4.6

OpenAI: o1 (batch)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons