GPT-3.5 Turbo vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 leads the LLM Stats Score 24.2 to -9.4. Qwen3-235B-A22B-Instruct-2507 is 3.7x cheaper per token.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3-235B-A22B-Instruct-2507 leads the overall LLM Stats Score 24.2 to -9.4, ranking #165 overall.

In the 1 individual benchmarks reported for both models, Qwen3-235B-A22B-Instruct-2507 wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Qwen3-235B-A22B-Instruct-2507 is roughly 3.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3-235B-A22B-Instruct-2507 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-3.5 Turbo

you want predictable pricing at $0.50/M input and $1.50/M output

Choose Qwen3-235B-A22B-Instruct-2507

overall performance matters — it scores 24.2 and ranks #165 on LLM Stats
your work emphasizes reasoning — it leads those capability indexes
you value its reported benchmark strengths — it wins 1 of 1 exact shared results
cost matters — it's about 3.7x cheaper per token
you process long inputs — it offers a 262,144 token context window
you want the most recent training data — it shipped Jul 2025
you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Better token value: Qwen3-235B-A22B-Instruct-2507

GPT-3.5 Turbo

OpenAI

Qwen3-235B-A22B-Instruct-2507

Alibaba Cloud / Qwen Team

Core performance indexes

LLM Stats Score

-9.4

#363 · 8 evals

24.2

#165 · 25 evals

Best

Reasoning

-8.7

#356 · 7 evals

23.9

#160 · 17 evals

Best

Coding

-4.5

#257 · 1 evals

4.2

#211 · 1 evals

Best

Cost, coverage & limits

Benchmark wins

0 of 1

1 of 1

Best

Input price

$0.50 / M

$0.09 / M

Best

Output price

$1.50 / M

$0.55 / M

Best

Context window

16,385

262,144

Best

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared

Index

GPT-3.5 Turbo

Qwen3-235B-A22B-Instruct-2507

Math

-2.3#309 · 5 evals

23.9#122 · 8 evals

Vision

-16.2#208 · 2 evals

9.1#132 · 2 evals

Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for GPT-3.5 Turbo · 25 for Qwen3-235B-A22B-Instruct-2507

1 shared

GPT-3.5 Turbo outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (GPQA).

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

Sun Sep 13 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Qwen3-235B-A22B-Instruct-2507 costs less

For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 5.6x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.09/1M tokens).

For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 2.7x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.55/1M tokens).

In conclusion, GPT-3.5 Turbo is more expensive than Qwen3-235B-A22B-Instruct-2507.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Sun Sep 13 2026 • llm-stats.com

GPT-3.5 Turbo

Input tokens$0.50

Output tokens$1.50

Best providerAzure

Qwen3-235B-A22B-Instruct-2507

Input tokens$0.09

Output tokens$0.55

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 262,144 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.

GPT-3.5 Turbo

Input16,385 tokens

Output4,096 tokens

Qwen3-235B-A22B-Instruct-2507

Input262,144 tokens

Output262,144 tokens

Sun Sep 13 2026 • llm-stats.com

License

Usage and distribution terms

GPT-3.5 Turbo is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GPT-3.5 Turbo

Proprietary

Closed source

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-3.5 Turbo was released on 2023-03-21, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 28 months newer than GPT-3.5 Turbo.

GPT-3.5 Turbo

Mar 21, 2023

3.5 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

1.1 years ago

2.3yr newer

Knowledge Cutoff

When training data ends

GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while Qwen3-235B-A22B-Instruct-2507's cutoff date is not specified.

We can confirm GPT-3.5 Turbo's training data extends to 2021-09-30, but cannot make a direct comparison without Qwen3-235B-A22B-Instruct-2507's cutoff date.

GPT-3.5 Turbo

Sep 2021

Qwen3-235B-A22B-Instruct-2507

—

Provider Availability

GPT-3.5 Turbo is available from Azure, OpenAI. Qwen3-235B-A22B-Instruct-2507 is available from DeepInfra, Fireworks, Novita.

GPT-3.5 Turbo

Azure

Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M

OpenAI

Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M

Qwen3-235B-A22B-Instruct-2507

Deepinfra

Input Price:Input: $0.09/1MOutput Price:Output: $0.55/1M

Fireworks

Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M

Novita

Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT-3.5 Turbo and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.

GPT-3.5 Turbo

✓ Preferred

Qwen3-235B-A22B-Instruct-2507

Open in Playground

FAQ

Common questions about GPT-3.5 Turbo vs Qwen3-235B-A22B-Instruct-2507.

Which is better, GPT-3.5 Turbo or Qwen3-235B-A22B-Instruct-2507?

Qwen3-235B-A22B-Instruct-2507 leads the LLM Stats Score 24.2 to -9.4. GPT-3.5 Turbo is made by OpenAI and Qwen3-235B-A22B-Instruct-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-3.5 Turbo compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

GPT-3.5 Turbo scores DROP: 70.2%, MMLU: 69.8%, HumanEval: 68.0%, MGSM: 56.3%, MATH: 43.1%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.

Is GPT-3.5 Turbo cheaper than Qwen3-235B-A22B-Instruct-2507?

Qwen3-235B-A22B-Instruct-2507 is 5.6x cheaper for input tokens. GPT-3.5 Turbo costs $0.50/M input and $1.50/M output via azure. Qwen3-235B-A22B-Instruct-2507 costs $0.09/M input and $0.55/M output via deepinfra.

What are the context window sizes for GPT-3.5 Turbo and Qwen3-235B-A22B-Instruct-2507?

GPT-3.5 Turbo supports 16K tokens and Qwen3-235B-A22B-Instruct-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-3.5 Turbo and Qwen3-235B-A22B-Instruct-2507?

Key differences include LLM Stats Score (-9.4 vs 24.2), context window (16K vs 262K), input pricing ($0.50 vs $0.09/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-3.5 Turbo and Qwen3-235B-A22B-Instruct-2507?

GPT-3.5 Turbo is developed by OpenAI and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.

GPT-3.5 Turbo vs Qwen3-235B-A22B-Instruct-2507