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

OpenAI: GPT-3.5 Turbo Instruct vs Qwen Image 2.0 Pro benchmark

Name: OpenAI: GPT-3.5 Turbo Instruct vs Qwen Image 2.0 Pro AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

Comparing verified benchmark accuracy, speed, and token pricing between OpenAI: GPT-3.5 Turbo Instruct and Qwen Image 2.0 Pro. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

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Executive Verdict Summary

OpenAI: GPT-3.5 Turbo Instruct holds empirical advantage (0 of 0 metrics)

Coding / SWESWE-bench

OpenAI: GPT-3.5 Turbo InstructTop code solve rate

ReasoningGPQA / Live

OpenAI: GPT-3.5 Turbo InstructTop logical accuracy

Best Value$/1M Tok

OpenAI: GPT-3.5 Turbo InstructLowest API billing cost

Speed / TokTok/Sec

OpenAI: GPT-3.5 Turbo InstructFastest stream rate

OpenAI

OpenAI: GPT-3.5 Turbo Instruct

Auto-discovered from OpenRouter (openai/gpt-3.5-turbo-instruct). Preview until a second source matches.

Alibaba

Qwen Image 2.0 Pro

Alibaba multimodal image synthesis foundation model with strong bilingual Chinese/English typography and cultural asset fidelity.

Img Elo 1,236$75/1k imgs

Top Rival Showdowns for OpenAI: GPT-3.5 Turbo Instruct

All Matchups

Compare vs:vs Reve 2.1 vs Nano Banana Pro (Gemini 3 Pro Image)vs FLUX.2 [max]vs Ideogram 4.0 (Quality)vs Recraft V4.1 Utility Pro

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.

OpenAI: GPT-3.5 Turbo Instruct (0)vsQwen Image 2.0 Pro (5)

OpenAI: GPT-3.5 Turbo Instruct: 0W (0%)Qwen Image 2.0 Pro: 5W (100%)

← OpenAI: GPT-3.5 Turbo InstructQwen Image 2.0 Pro →

🏆Qwen Image 2.0 Pro Leads(3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Benchmark

OpenAI: GPT-3.5 Turbo InstructvsQwen Image 2.0 Pro

Image Elo

—vs1,236

Prompt adherence

—vs90.8%

Text rendering

—vs92%

OpenAI: GPT-3.5 Turbo Instruct: 0WQwen Image 2.0 Pro: 3W

🏆Qwen Image 2.0 Pro Leads(1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Benchmark

OpenAI: GPT-3.5 Turbo InstructvsQwen Image 2.0 Pro

Generation time

—vs3.6s

OpenAI: GPT-3.5 Turbo Instruct: 0WQwen Image 2.0 Pro: 1W

🏆Qwen Image 2.0 Pro Leads(1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Benchmark

OpenAI: GPT-3.5 Turbo InstructvsQwen Image 2.0 Pro

Price per 1k images

—vs$75/1k

OpenAI: GPT-3.5 Turbo Instruct: 0WQwen Image 2.0 Pro: 1W

Side-by-Side Benchmark Matrix

OpenAI: GPT-3.5 Turbo InstructQwen Image 2.0 Pro

Image Elo

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro1,236

Generation time

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro3.6s

Price per 1k images

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro$75/1k

Prompt adherence

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro90.8%

Text rendering

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro92%

Benchmark	OpenAI: GPT-3.5 Turbo Instruct	Qwen Image 2.0 Pro	Advantage Delta
Image Elo	—	1,236 seed-bootstrap · Aug 1, 2026	—
Generation time	—	3.6s seed-bootstrap · Aug 1, 2026	—
Price per 1k images	—	$75/1k seed-bootstrap · Aug 1, 2026	—
Prompt adherence	—	90.8% seed-bootstrap · Aug 1, 2026	—
Text rendering	—	92% seed-bootstrap · Aug 1, 2026	—

Workload Cost & Savings Calculator

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

Save 100% with OpenAI: GPT-3.5 Turbo Instruct

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

OpenAI: GPT-3.5 Turbo Instruct$0.00 / mo

Rate: $0/1k

Qwen Image 2.0 Pro$1,875.00 / mo

Rate: $75/1k

Estimated Cost Delta

OpenAI: GPT-3.5 Turbo Instruct is estimated to save $1,875.00/month ($22,500/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 / visionQwen Image 2.0 Pro

Qwen Image 2.0 Pro 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	Qwen Image 2.0 Pro	Qwen Image 2.0 Pro is the side marked multimodal in the catalog.

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!

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

OpenAI

OpenAI: GPT-3.5 Turbo Instruct

Elo n/a

SWE-bench—

Speed (tok/s)4k

Input / 1M Tokens$1.5/1M

Output / 1M Tokens$2/1M

Alibaba

Qwen Image 2.0 Pro

Elo n/a

SWE-bench—

Speed (tok/s)—

Input / 1M Tokens$75/1k

Output / 1M Tokens$75/1k

Frequently Asked Questions

Which is better overall, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?: 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, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?: 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, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?: 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. OpenAI: GPT-3.5 Turbo Instruct and Qwen Image 2.0 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All OpenAI: GPT-3.5 Turbo Instruct matchups →|All Qwen Image 2.0 Pro matchups →

GPT Image 2 (High) vs Qwen Image 2.0 Pro GPT Image 2 (Low / Fast) vs Qwen Image 2.0 Pro GPT Image 1.5 vs Qwen Image 2.0 Pro DALL-E 3 vs Qwen Image 2.0 Pro Reve 2.1 vs Qwen Image 2.0 Pro Nano Banana Pro (Gemini 3 Pro Image) vs Qwen Image 2.0 Pro

Side-by-Side Benchmark Matrix

OpenAI: GPT-3.5 Turbo InstructQwen Image 2.0 Pro

Image Elo

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro1,236

Generation time

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro3.6s

Price per 1k images

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro$75/1k

Prompt adherence

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro90.8%

Text rendering

OpenAI: GPT-3.5 Turbo Instruct—

Qwen Image 2.0 Pro92%

Benchmark	OpenAI: GPT-3.5 Turbo Instruct	Qwen Image 2.0 Pro	Advantage Delta
Image Elo	—	1,236 seed-bootstrap · Aug 1, 2026	—
Generation time	—	3.6s seed-bootstrap · Aug 1, 2026	—
Price per 1k images	—	$75/1k seed-bootstrap · Aug 1, 2026	—
Prompt adherence	—	90.8% seed-bootstrap · Aug 1, 2026	—
Text rendering	—	92% 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 / visionQwen Image 2.0 Pro

Qwen Image 2.0 Pro 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	Qwen Image 2.0 Pro	Qwen Image 2.0 Pro is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?

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, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?

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, OpenAI: GPT-3.5 Turbo Instruct or Qwen Image 2.0 Pro?

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. OpenAI: GPT-3.5 Turbo Instruct and Qwen Image 2.0 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.