GPT-3.5 Turbo vs QwQ-32B-Preview
QwQ-32B-Preview leads the LLM Stats Score 9.3 to -9.2. QwQ-32B-Preview is 4.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
QwQ-32B-Preview leads the overall LLM Stats Score 9.3 to -9.2, ranking #258 overall.
In the 1 individual benchmarks reported for both models, QwQ-32B-Preview wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, QwQ-32B-Preview is roughly 4.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
QwQ-32B-Preview also accepts a larger context window (32,768 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 QwQ-32B-Preview
- overall performance matters — it scores 9.3 and ranks #258 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 4.6x cheaper per token
- you process long inputs — it offers a 32,768 token context window
- you want the most recent training data — it shipped Nov 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for GPT-3.5 Turbo · 4 for QwQ-32B-Preview
GPT-3.5 Turbo outperforms in 0 benchmarks, while QwQ-32B-Preview is better at 1 benchmark (GPQA).
QwQ-32B-Preview significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 3.3x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 7.5x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, GPT-3.5 Turbo is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
QwQ-32B-Preview accepts 32,768 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. QwQ-32B-Preview can generate longer responses up to 32,768 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
License
Usage and distribution terms
GPT-3.5 Turbo is licensed under a proprietary license, while QwQ-32B-Preview uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-3.5 Turbo was released on 2023-03-21, while QwQ-32B-Preview was released on 2024-11-28.
QwQ-32B-Preview is 21 months newer than GPT-3.5 Turbo.
Mar 21, 2023
3.5 years ago
Nov 28, 2024
1.8 years ago
1.7yr newerKnowledge Cutoff
When training data ends
GPT-3.5 Turbo has a knowledge cutoff of 2021-09-30, while QwQ-32B-Preview has a cutoff of 2024-11-28.
QwQ-32B-Preview has more recent training data (up to 2024-11-28), making it potentially better informed about events through that date compared to GPT-3.5 Turbo (2021-09-30).
Sep 2021
Nov 2024
3.2 yr newerProvider Availability
GPT-3.5 Turbo is available from Azure, OpenAI. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
GPT-3.5 Turbo
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-3.5 Turbo and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-3.5 Turbo vs QwQ-32B-Preview.