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

Qwen: Qwen3.8 Max vs Wan2.6 Text to Image benchmark

Name: Qwen: Qwen3.8 Max vs Wan2.6 Text to Image AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

Comparing verified benchmark accuracy, speed, and token pricing between Qwen: Qwen3.8 Max and Wan2.6 Text to Image. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

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Executive Verdict Summary

Qwen: Qwen3.8 Max holds empirical advantage (0 of 0 metrics)

Coding / SWESWE-bench

Qwen: Qwen3.8 MaxTop code solve rate

ReasoningGPQA / Live

Qwen: Qwen3.8 MaxTop logical accuracy

Best Value$/1M Tok

Qwen: Qwen3.8 MaxLowest API billing cost

Speed / TokTok/Sec

Qwen: Qwen3.8 MaxFastest stream rate

Alibaba

Qwen: Qwen3.8 Max

Auto-discovered from OpenRouter (qwen/qwen3.8-max). Preview until a second source matches.

Alibaba

Wan2.6 Text to Image

Alibaba high-efficiency open video/image unified transformer backbone.

Img Elo 1,215$30/1k imgs

Top Rival Showdowns for Qwen: Qwen3.8 Max

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.

Qwen: Qwen3.8 Max (0)vsWan2.6 Text to Image (5)

Qwen: Qwen3.8 Max: 0W (0%)Wan2.6 Text to Image: 5W (100%)

← Qwen: Qwen3.8 MaxWan2.6 Text to Image →

🏆Wan2.6 Text to Image Leads(3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Benchmark

Qwen: Qwen3.8 MaxvsWan2.6 Text to Image

Image Elo

—vs1,215

Prompt adherence

—vs89.5%

Text rendering

—vs87%

Qwen: Qwen3.8 Max: 0WWan2.6 Text to Image: 3W

🏆Wan2.6 Text to Image Leads(1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Benchmark

Qwen: Qwen3.8 MaxvsWan2.6 Text to Image

Generation time

—vs3.1s

Qwen: Qwen3.8 Max: 0WWan2.6 Text to Image: 1W

🏆Wan2.6 Text to Image Leads(1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Benchmark

Qwen: Qwen3.8 MaxvsWan2.6 Text to Image

Price per 1k images

—vs$30/1k

Qwen: Qwen3.8 Max: 0WWan2.6 Text to Image: 1W

Side-by-Side Benchmark Matrix

Qwen: Qwen3.8 MaxWan2.6 Text to Image

Image Elo

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image1,215

Generation time

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image3.1s

Price per 1k images

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image$30/1k

Prompt adherence

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image89.5%

Text rendering

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image87%

Benchmark	Qwen: Qwen3.8 Max	Wan2.6 Text to Image	Advantage Delta
Image Elo	—	1,215 seed-bootstrap · Aug 1, 2026	—
Generation time	—	3.1s seed-bootstrap · Aug 1, 2026	—
Price per 1k images	—	$30/1k seed-bootstrap · Aug 1, 2026	—
Prompt adherence	—	89.5% seed-bootstrap · Aug 1, 2026	—
Text rendering	—	87% seed-bootstrap · Aug 1, 2026	—

Workload Cost & Savings Calculator

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

Save 100% with Qwen: Qwen3.8 Max

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

Qwen: Qwen3.8 Max$0.00 / mo

Rate: $0/1k

Wan2.6 Text to Image$750.00 / mo

Rate: $30/1k

Estimated Cost Delta

Qwen: Qwen3.8 Max is estimated to save $750.00/month ($9,000/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 / visionWan2.6 Text to Image

Wan2.6 Text to Image 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	Wan2.6 Text to Image	Wan2.6 Text to Image is the side marked multimodal in the catalog.

Cast Your Matchup Vote

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Community Discussions (0)

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Alibaba

Qwen: Qwen3.8 Max

Elo n/a

SWE-bench—

Speed (tok/s)1M

Input / 1M Tokens$2/1M

Output / 1M Tokens$6/1M

Alibaba

Wan2.6 Text to Image

Elo n/a

SWE-bench—

Speed (tok/s)—

Input / 1M Tokens$30/1k

Output / 1M Tokens$30/1k

Frequently Asked Questions

Which is better overall, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?: 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, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?: 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, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?: 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?: Wan2.6 Text to Image is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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. Qwen: Qwen3.8 Max and Wan2.6 Text to Image Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Qwen: Qwen3.8 Max matchups →|All Wan2.6 Text to Image matchups →

Qwen Image 2.0 Pro vs Wan2.6 Text to Image GPT Image 2 (High) vs Wan2.6 Text to Image Reve 2.1 vs Wan2.6 Text to Image Nano Banana Pro (Gemini 3 Pro Image) vs Wan2.6 Text to Image Nano Banana 2 (Gemini 3.1 Flash Image) vs Wan2.6 Text to Image FLUX.2 [max] vs Wan2.6 Text to Image

Side-by-Side Benchmark Matrix

Qwen: Qwen3.8 MaxWan2.6 Text to Image

Image Elo

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image1,215

Generation time

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image3.1s

Price per 1k images

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image$30/1k

Prompt adherence

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image89.5%

Text rendering

Qwen: Qwen3.8 Max—

Wan2.6 Text to Image87%

Benchmark

Qwen: Qwen3.8 Max

Wan2.6 Text to Image

Advantage Delta

Image Elo

—

1,215

seed-bootstrap · Aug 1, 2026

—

Generation time

—

3.1s

seed-bootstrap · Aug 1, 2026

—

Price per 1k images

—

$30/1k

seed-bootstrap · Aug 1, 2026

—

Prompt adherence

—

89.5%

seed-bootstrap · Aug 1, 2026

—

Text rendering

—

87%

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 / visionWan2.6 Text to Image

Wan2.6 Text to Image 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	Wan2.6 Text to Image	Wan2.6 Text to Image is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?

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, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?

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, Qwen: Qwen3.8 Max or Wan2.6 Text to Image?

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?

Wan2.6 Text to Image is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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. Qwen: Qwen3.8 Max and Wan2.6 Text to Image Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.