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

Claude Opus 4 vs inclusionAI: Ling-2.6-flash benchmark

Name: Claude Opus 4 vs inclusionAI: Ling-2.6-flash AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude Opus 4 (Anthropic) and inclusionAI: Ling-2.6-flash (inclusionai) using the latest snapshots we have as of Aug 17, 2026. inclusionAI: Ling-2.6-flash wins on output price at $0.03/1M. inclusionAI: Ling-2.6-flash has the larger context window (262k 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.

Share Analysis:

WhatsApp Telegram X / Post LinkedIn Reddit

Anthropic

Claude Opus 4

First Claude 4 Opus generation. Baseline for opus 4 vs opus 5.

Elo 1,490$75/1M out

inclusionai

inclusionAI: Ling-2.6-flash

Auto-discovered from OpenRouter (inclusionai/ling-2.6-flash). Preview until a second source matches.

$0.03/1M out

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

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 Opus 4 (7)vsinclusionAI: Ling-2.6-flash (3)

Claude Opus 4: 7W (70%)Overall: Claude Opus 4inclusionAI: Ling-2.6-flash: 3W (30%)

← Claude Opus 4inclusionAI: Ling-2.6-flash →

Claude Opus 4 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs—

Coding Elo

1,502vs—

SWE-bench

72.5%vs—

LiveBench

66.8%vs—

GPQA Diamond

80.4%vs—

Claude Opus 4: 5WinclusionAI: Ling-2.6-flash: 0W

Claude Opus 4 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

58 tok/svs—

Time to first token

390 msvs—

Claude Opus 4: 2WinclusionAI: Ling-2.6-flash: 0W

inclusionAI: Ling-2.6-flash (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$0.03/1M

Input price

$15/1Mvs$0.01/1M

Context window

200kvs262k

Claude Opus 4: 0WinclusionAI: Ling-2.6-flash: 3W

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 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

inclusionAI: Ling-2.6-flash

$74.97/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,490

EloHigh is better

—

Code Elo

High is better

1,502

Code EloHigh is better

—

LiveBench

High is better

66.8%

LiveBenchHigh is better

—

SWE-bench

High is better

72.5%

SWE-benchHigh is better

—

GPQA

High is better

80.4%

GPQAHigh is better

—

TTFT

Low is better

390 ms

TTFTLow is better

—

Speed

High is better

58 tok/s

SpeedHigh is better

—

In $

Low is better

$15.00 / 1M

In $Low is better

$0.01 / 1M+149900%

Out $

Low is better

$75.00 / 1M

Out $Low is better

$0.03 / 1M+249900%

Context

High is better

200k

ContextHigh is better

262k+31%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 100% with inclusionAI: Ling-2.6-flash

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$1,650.00 / mo

In: $525Out: $1,125

inclusionAI: Ling-2.6-flash$0.80 / mo

In: $0.35Out: $0.45

Estimated Cost Delta

inclusionAI: Ling-2.6-flash is estimated to save $1,649.20/month ($19,790/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
inclusionAI: Ling-2.6-flash:Pick inclusionAI: Ling-2.6-flash when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinclusionAI: Ling-2.6-flash

Lower output list price ($0.03/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinclusionAI: Ling-2.6-flash

Larger window (262k).

Screenshots / visionClaude Opus 4

Claude Opus 4 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	inclusionAI: Ling-2.6-flash	Lower output list price ($0.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	inclusionAI: Ling-2.6-flash	Larger window (262k).
Screenshots / vision	Claude Opus 4	Claude Opus 4 is the side marked multimodal in the catalog.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

Share card

The real PNG is generated at /compare/claude-opus-4-vs-ling-2-6-flash/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

Anthropic

Claude Opus 4

Elo 1,490

LiveBench66.8%

SWE-bench72.5%

Speed58 tok/s

Output cost$75/1M

inclusionai

inclusionAI: Ling-2.6-flash

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.03/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4 or inclusionAI: Ling-2.6-flash?: 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 or inclusionAI: Ling-2.6-flash?: 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?: inclusionAI: Ling-2.6-flash output tokens are $0.03/1M versus $75/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4 or inclusionAI: Ling-2.6-flash?: We do not have TTFT for both models.
Which has the larger context window?: inclusionAI: Ling-2.6-flash accepts 262k 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 and inclusionAI: Ling-2.6-flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude Opus 4 matchups →|All inclusionAI: Ling-2.6-flash matchups →

Claude Opus 4 vs Claude 3 Opus (previous opus)Claude Opus 4 vs Claude Opus 4.5 (next opus)Claude Sonnet 4.5 vs Claude Opus 4 Claude Sonnet 5 vs Claude Opus 4 Claude Opus 4.6 vs Claude Opus 4 Claude Opus 4.8 vs Claude Opus 4

Claude Opus 4 vs inclusionAI: Ling-2.6-flash benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4 (7)vsinclusionAI: Ling-2.6-flash (3)

Claude Opus 4: 7W (70%)Overall: Claude Opus 4inclusionAI: Ling-2.6-flash: 3W (30%)

← Claude Opus 4inclusionAI: Ling-2.6-flash →

Claude Opus 4 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs—

Coding Elo

1,502vs—

SWE-bench

72.5%vs—

LiveBench

66.8%vs—

GPQA Diamond

80.4%vs—

Claude Opus 4: 5WinclusionAI: Ling-2.6-flash: 0W

Claude Opus 4 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

58 tok/svs—

Time to first token

390 msvs—

Claude Opus 4: 2WinclusionAI: Ling-2.6-flash: 0W

inclusionAI: Ling-2.6-flash (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$0.03/1M

Input price

$15/1Mvs$0.01/1M

Context window

200kvs262k

Claude Opus 4: 0WinclusionAI: Ling-2.6-flash: 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinclusionAI: Ling-2.6-flash

Lower output list price ($0.03/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinclusionAI: Ling-2.6-flash

Larger window (262k).

Screenshots / visionClaude Opus 4

Claude Opus 4 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	inclusionAI: Ling-2.6-flash	Lower output list price ($0.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	inclusionAI: Ling-2.6-flash	Larger window (262k).
Screenshots / vision	Claude Opus 4	Claude Opus 4 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude Opus 4 or inclusionAI: Ling-2.6-flash?

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 or inclusionAI: Ling-2.6-flash?

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?

inclusionAI: Ling-2.6-flash output tokens are $0.03/1M versus $75/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude Opus 4 or inclusionAI: Ling-2.6-flash?

We do not have TTFT for both models.

Which has the larger context window?

inclusionAI: Ling-2.6-flash accepts 262k 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 and inclusionAI: Ling-2.6-flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.