Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Claude Opus 4.6 vs Qwen: Qwen2.5 VL 72B Instruct benchmark

Name: Claude Opus 4.6 vs Qwen: Qwen2.5 VL 72B Instruct AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude Opus 4.6 (Anthropic) and Qwen: Qwen2.5 VL 72B Instruct (Alibaba) using the latest snapshots we have as of Aug 17, 2026. Qwen: Qwen2.5 VL 72B Instruct wins on output price at $1/1M. 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

Alibaba

Qwen: Qwen2.5 VL 72B Instruct

Auto-discovered from OpenRouter (qwen/qwen2.5-vl-72b-instruct). Preview until a second source matches.

$1/1M out

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Instant pairwise benchmark recalculation across 400+ LLMs

Model A

Model B

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 (8)vsQwen: Qwen2.5 VL 72B Instruct (2)

Claude Opus 4.6: 8W (80%)Overall: Claude Opus 4.6Qwen: Qwen2.5 VL 72B Instruct: 2W (20%)

← Claude Opus 4.6Qwen: Qwen2.5 VL 72B Instruct →

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: 5WQwen: Qwen2.5 VL 72B Instruct: 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: 2WQwen: Qwen2.5 VL 72B Instruct: 0W

Qwen: Qwen2.5 VL 72B Instruct (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$1/1M

Input price

$5/1Mvs$0.8/1M

Context window

1Mvs128k

Claude Opus 4.6: 1WQwen: Qwen2.5 VL 72B Instruct: 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 AdvantageClaude Opus 4.6 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Qwen: Qwen2.5 VL 72B Instruct

$24.00/1M 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

$5/1M

In $Low is better

$0.8/1M+525%

Out $

Low is better

$25/1M

Out $Low is better

$1/1M+2400%

Context

High is better

+681%1M

ContextHigh is better

128k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 92% with Qwen: Qwen2.5 VL 72B Instruct

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

Qwen: Qwen2.5 VL 72B Instruct$43.00 / mo

In: $28.00Out: $15.00

Estimated Cost Delta

Qwen: Qwen2.5 VL 72B Instruct is estimated to save $507.00/month ($6,084/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen: Qwen2.5 VL 72B Instruct:Pick Qwen: Qwen2.5 VL 72B Instruct 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 chatQwen: Qwen2.5 VL 72B Instruct

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

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	Qwen: Qwen2.5 VL 72B Instruct	Lower output list price ($1/1M).
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.

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CompareLLM Matrix

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LIVE

Anthropic

Claude Opus 4.6

Elo 1,574

LiveBench72%

SWE-bench75.9%

Speed64 tok/s

Output cost$25/1M

Alibaba

Qwen: Qwen2.5 VL 72B Instruct

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$1/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or Qwen: Qwen2.5 VL 72B Instruct?: 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 Qwen: Qwen2.5 VL 72B Instruct?: 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?: Qwen: Qwen2.5 VL 72B Instruct output tokens are $1/1M versus $25/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4.6 or Qwen: Qwen2.5 VL 72B Instruct?: We do not have TTFT for both models.
Which has the larger context window?: Claude Opus 4.6 accepts 1M 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 Opus 4.6 and Qwen: Qwen2.5 VL 72B Instruct 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 Qwen: Qwen2.5 VL 72B Instruct matchups →

Claude Opus 4.6 vs Claude Opus 4.5 (previous opus)Claude Opus 4.6 vs Claude Opus 4.8 (next opus)Claude Sonnet 5 vs Claude Opus 4.6 Claude Fable 5 vs Claude Opus 4.6 Claude Sonnet 4.5 vs Claude Opus 4.6 Claude Opus 5 vs Claude Opus 4.6

Claude Opus 4.6 vs Qwen: Qwen2.5 VL 72B Instruct benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (8)vsQwen: Qwen2.5 VL 72B Instruct (2)

Claude Opus 4.6: 8W (80%)Overall: Claude Opus 4.6Qwen: Qwen2.5 VL 72B Instruct: 2W (20%)

← Claude Opus 4.6Qwen: Qwen2.5 VL 72B Instruct →

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: 5WQwen: Qwen2.5 VL 72B Instruct: 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: 2WQwen: Qwen2.5 VL 72B Instruct: 0W

Qwen: Qwen2.5 VL 72B Instruct (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$1/1M

Input price

$5/1Mvs$0.8/1M

Context window

1Mvs128k

Claude Opus 4.6: 1WQwen: Qwen2.5 VL 72B Instruct: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatQwen: Qwen2.5 VL 72B Instruct

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

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	Qwen: Qwen2.5 VL 72B Instruct	Lower output list price ($1/1M).
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 Qwen: Qwen2.5 VL 72B Instruct?

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 Qwen: Qwen2.5 VL 72B Instruct?

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?

Qwen: Qwen2.5 VL 72B Instruct output tokens are $1/1M versus $25/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude Opus 4.6 or Qwen: Qwen2.5 VL 72B Instruct?

We do not have TTFT for both models.

Which has the larger context window?

Claude Opus 4.6 accepts 1M 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 Opus 4.6 and Qwen: Qwen2.5 VL 72B Instruct 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

Qwen: Qwen2.5 VL 72B Instruct

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)

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CompareLLM Matrix

Claude Opus 4.6

Qwen: Qwen2.5 VL 72B Instruct

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

Qwen: Qwen2.5 VL 72B Instruct

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

Qwen: Qwen2.5 VL 72B Instruct

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons