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

MAI-Image-2.5 vs Qwen: Qwen3 Next 80B A3B Thinking benchmark

Name: MAI-Image-2.5 vs Qwen: Qwen3 Next 80B A3B Thinking AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

Comparing verified benchmark accuracy, speed, and token pricing between MAI-Image-2.5 and Qwen: Qwen3 Next 80B A3B Thinking. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

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Executive Verdict Summary

MAI-Image-2.5 holds empirical advantage (0 of 0 metrics)

Coding / SWESWE-bench

MAI-Image-2.5Top code solve rate

ReasoningGPQA / Live

MAI-Image-2.5Top logical accuracy

Best Value$/1M Tok

Qwen: Qwen3 Next 80B A3B ThinkingLowest API billing cost

Speed / TokTok/Sec

MAI-Image-2.5Fastest stream rate

Microsoft AI

MAI-Image-2.5

Microsoft AI proprietary foundation image model for Copilot Studio and enterprise creative workflows.

Img Elo 1,307$48.1/1k imgs

Alibaba

Qwen: Qwen3 Next 80B A3B Thinking

Auto-discovered from OpenRouter (qwen/qwen3-next-80b-a3b-thinking). Preview until a second source matches.

Top Rival Showdowns for MAI-Image-2.5

All Matchups

Compare vs:vs GPT Image 2 (High)vs Reve 2.1 vs Nano Banana Pro (Gemini 3 Pro Image)vs FLUX.2 [max]vs Ideogram 4.0 (Quality)

Image Quality Leader

No shared data

Single model data

Generation Speed Leader

No shared data

No latency data

Value per Dollar Leader

No shared data

Unpriced

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

MAI-Image-2.5 (5)vsQwen: Qwen3 Next 80B A3B Thinking (0)

MAI-Image-2.5: 5W (100%)Qwen: Qwen3 Next 80B A3B Thinking: 0W (0%)

← MAI-Image-2.5Qwen: Qwen3 Next 80B A3B Thinking →

🏆MAI-Image-2.5 Leads(3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Benchmark

MAI-Image-2.5vsQwen: Qwen3 Next 80B A3B Thinking

Image Elo

1,307vs—

Prompt adherence

92%vs—

Text rendering

93%vs—

MAI-Image-2.5: 3WQwen: Qwen3 Next 80B A3B Thinking: 0W

🏆MAI-Image-2.5 Leads(1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Benchmark

MAI-Image-2.5vsQwen: Qwen3 Next 80B A3B Thinking

Generation time

3.8svs—

MAI-Image-2.5: 1WQwen: Qwen3 Next 80B A3B Thinking: 0W

🏆MAI-Image-2.5 Leads(1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Benchmark

MAI-Image-2.5vsQwen: Qwen3 Next 80B A3B Thinking

Price per 1k images

$48.1/1kvs—

MAI-Image-2.5: 1WQwen: Qwen3 Next 80B A3B Thinking: 0W

Side-by-Side Benchmark Matrix

MAI-Image-2.5Qwen: Qwen3 Next 80B A3B Thinking

Image Elo

MAI-Image-2.51,307

Qwen: Qwen3 Next 80B A3B Thinking—

Generation time

MAI-Image-2.53.8s

Qwen: Qwen3 Next 80B A3B Thinking—

Price per 1k images

MAI-Image-2.5$48.1/1k

Qwen: Qwen3 Next 80B A3B Thinking—

Prompt adherence

MAI-Image-2.592%

Qwen: Qwen3 Next 80B A3B Thinking—

Text rendering

MAI-Image-2.593%

Qwen: Qwen3 Next 80B A3B Thinking—

Benchmark	MAI-Image-2.5	Qwen: Qwen3 Next 80B A3B Thinking	Advantage Delta
Image Elo	1,307 seed-bootstrap · Aug 1, 2026	—	—
Generation time	3.8s seed-bootstrap · Aug 1, 2026	—	—
Price per 1k images	$48.1/1k seed-bootstrap · Aug 1, 2026	—	—
Prompt adherence	92% seed-bootstrap · Aug 1, 2026	—	—
Text rendering	93% seed-bootstrap · Aug 1, 2026	—	—

Workload Cost & Savings Calculator

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

Save 100% with Qwen: Qwen3 Next 80B A3B Thinking

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

MAI-Image-2.5$1,202.50 / mo

Rate: $48.1/1k

Qwen: Qwen3 Next 80B A3B Thinking$0.00 / mo

Rate: $0/1k

Estimated Cost Delta

Qwen: Qwen3 Next 80B A3B Thinking is estimated to save $1,202.50/month ($14,430/year).

Based on 25k images generated

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visionMAI-Image-2.5

MAI-Image-2.5 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	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	MAI-Image-2.5	MAI-Image-2.5 is the side marked multimodal in the catalog.

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Microsoft AI

MAI-Image-2.5

Elo n/a

SWE-bench—

Speed (tok/s)—

Input / 1M Tokens$48.1/1k

Output / 1M Tokens$48.1/1k

Alibaba

Qwen: Qwen3 Next 80B A3B Thinking

Elo n/a

SWE-bench—

Speed (tok/s)262k

Input / 1M Tokens$0.15/1M

Output / 1M Tokens$1.2/1M

Frequently Asked Questions

Which is better overall, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?: 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, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?: 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?: List prices are missing for at least one model.
Which is faster, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?: We do not have TTFT for both models.
Which has the larger context window?: Context window is missing for at least one model.
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. MAI-Image-2.5 and Qwen: Qwen3 Next 80B A3B Thinking Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All MAI-Image-2.5 matchups →|All Qwen: Qwen3 Next 80B A3B Thinking matchups →

MAI-Image-2.5 vs HiDream-O1-Image-1.5 (previous other)MAI-Image-2.5 vs MAI-Image-2.5-Flash (next other)

Side-by-Side Benchmark Matrix

MAI-Image-2.5Qwen: Qwen3 Next 80B A3B Thinking

Image Elo

MAI-Image-2.51,307

Qwen: Qwen3 Next 80B A3B Thinking—

Generation time

MAI-Image-2.53.8s

Qwen: Qwen3 Next 80B A3B Thinking—

Price per 1k images

MAI-Image-2.5$48.1/1k

Qwen: Qwen3 Next 80B A3B Thinking—

Prompt adherence

MAI-Image-2.592%

Qwen: Qwen3 Next 80B A3B Thinking—

Text rendering

MAI-Image-2.593%

Qwen: Qwen3 Next 80B A3B Thinking—

Benchmark	MAI-Image-2.5	Qwen: Qwen3 Next 80B A3B Thinking	Advantage Delta
Image Elo	1,307 seed-bootstrap · Aug 1, 2026	—	—
Generation time	3.8s seed-bootstrap · Aug 1, 2026	—	—
Price per 1k images	$48.1/1k seed-bootstrap · Aug 1, 2026	—	—
Prompt adherence	92% seed-bootstrap · Aug 1, 2026	—	—
Text rendering	93% seed-bootstrap · Aug 1, 2026	—	—

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visionMAI-Image-2.5

MAI-Image-2.5 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	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	MAI-Image-2.5	MAI-Image-2.5 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?

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, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?

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?

List prices are missing for at least one model.

Which is faster, MAI-Image-2.5 or Qwen: Qwen3 Next 80B A3B Thinking?

We do not have TTFT for both models.

Which has the larger context window?

Context window is missing for at least one model.

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. MAI-Image-2.5 and Qwen: Qwen3 Next 80B A3B Thinking Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.