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

MAI-Image-2.5-Flash vs Qwen2.5 Coder 32B Instruct benchmark

Name: MAI-Image-2.5-Flash vs Qwen2.5 Coder 32B Instruct AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MAI-Image-2.5-Flash (Microsoft AI) and Qwen2.5 Coder 32B Instruct (Alibaba) using the latest snapshots we have as of Aug 17, 2026. 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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Microsoft AI

MAI-Image-2.5-Flash

Cost-optimized Microsoft AI image model delivering sub-2 second responses at $20/1k images.

FlashImg Elo 1,231$20/1k imgs

Alibaba

Qwen2.5 Coder 32B Instruct

Auto-discovered from OpenRouter (qwen/qwen-2.5-coder-32b-instruct). Preview until a second source matches.

Img Elo 1,425

Model Lineage & Multi-Tier Derivatives

MAI-Image Series Family (2 models)

Compare vs Base (MAI-Image-2.5)

MAI-Image-2.5

Microsoft AI

Flagship Base

Elo

1307

Latency

3.8s

Price

$48.1/1k

View model →vs this

MAI-Image-2.5-Flash

Microsoft AI

Flash

Elo

1231

Latency

1.6s

Price

$20/1k

-76 Elo-58% cost

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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.

MAI-Image-2.5-Flash (5)vsQwen2.5 Coder 32B Instruct (0)

MAI-Image-2.5-Flash: 5W (100%)Overall: MAI-Image-2.5-FlashQwen2.5 Coder 32B Instruct: 0W (0%)

← MAI-Image-2.5-FlashQwen2.5 Coder 32B Instruct →

MAI-Image-2.5-Flash (3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Image Elo

1,231vs—

Prompt adherence

88.5%vs—

Text rendering

89%vs—

MAI-Image-2.5-Flash: 3WQwen2.5 Coder 32B Instruct: 0W

MAI-Image-2.5-Flash (1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Generation time

1.6svs—

MAI-Image-2.5-Flash: 1WQwen2.5 Coder 32B Instruct: 0W

MAI-Image-2.5-Flash (1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Price per 1k images

$20/1kvs—

MAI-Image-2.5-Flash: 1WQwen2.5 Coder 32B Instruct: 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 AdvantageMAI-Image-2.5-Flash 5/6

Image Preference Elo

No shared data

Generation Latency

No shared data

Image Price Efficiency

No shared data

Full Benchmark Score Matrix

—

Img Elo

High is better

1,231

Img EloHigh is better

—

Gen Time

Low is better

1.6s

Gen TimeLow is better

—

Img $

Low is better

$20/1k

Img $Low is better

—

Prompt %

High is better

88.5%

Prompt %High is better

—

Text %

High is better

89%

Text %High is better

—

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 100% with Qwen2.5 Coder 32B Instruct

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

MAI-Image-2.5-Flash$500.00 / mo

Rate: $20/1k

Qwen2.5 Coder 32B Instruct$0.00 / mo

Rate: $0/1k

Estimated Cost Delta

Qwen2.5 Coder 32B Instruct is estimated to save $500.00/month ($6,000/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-Flash

MAI-Image-2.5-Flash 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-Flash	MAI-Image-2.5-Flash is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

Microsoft AI

MAI-Image-2.5-Flash

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost—

Alibaba

Qwen2.5 Coder 32B Instruct

Elo 1,425

LiveBench64.8%

SWE-bench65.2%

Speed—

Output cost$1/1M

Frequently Asked Questions

Which is better overall, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B 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, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B 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?: List prices are missing for at least one model.
Which is faster, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B Instruct?: 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-Flash and Qwen2.5 Coder 32B Instruct 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-Flash matchups →|All Qwen2.5 Coder 32B Instruct matchups →

MAI-Image-2.5-Flash vs MAI-Image-2.5 (previous other)Qwen2.5 Coder 32B Instruct vs Qwen 2.5 Plus (next qwen)Qwen 3 Max vs Qwen2.5 Coder 32B Instruct Qwen Image 2.0 Pro vs MAI-Image-2.5-Flash Qwen QwQ 32B vs Qwen2.5 Coder 32B Instruct Claude Opus 4.5 vs Qwen2.5 Coder 32B Instruct

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MAI-Image-2.5-Flash (5)vsQwen2.5 Coder 32B Instruct (0)

MAI-Image-2.5-Flash: 5W (100%)Overall: MAI-Image-2.5-FlashQwen2.5 Coder 32B Instruct: 0W (0%)

← MAI-Image-2.5-FlashQwen2.5 Coder 32B Instruct →

MAI-Image-2.5-Flash (3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Image Elo

1,231vs—

Prompt adherence

88.5%vs—

Text rendering

89%vs—

MAI-Image-2.5-Flash: 3WQwen2.5 Coder 32B Instruct: 0W

MAI-Image-2.5-Flash (1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Generation time

1.6svs—

MAI-Image-2.5-Flash: 1WQwen2.5 Coder 32B Instruct: 0W

MAI-Image-2.5-Flash (1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Price per 1k images

$20/1kvs—

MAI-Image-2.5-Flash: 1WQwen2.5 Coder 32B Instruct: 0W

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-Flash

MAI-Image-2.5-Flash 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-Flash	MAI-Image-2.5-Flash is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B 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, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B 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?

List prices are missing for at least one model.

Which is faster, MAI-Image-2.5-Flash or Qwen2.5 Coder 32B Instruct?

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-Flash and Qwen2.5 Coder 32B Instruct Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.