DeepSeek-V3.2-Exp vs GPT-3.5 Turbo
DeepSeek-V3.2-Exp leads the LLM Stats Score 28.5 to -9.3. DeepSeek-V3.2-Exp is 2.5x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3.2-Exp leads the overall LLM Stats Score 28.5 to -9.3, ranking #125 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V3.2-Exp wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Exp is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2-Exp also accepts a larger context window (163,840 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 DeepSeek-V3.2-Exp
- overall performance matters — it scores 28.5 and ranks #125 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 2.5x cheaper per token
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose GPT-3.5 Turbo
- you want predictable pricing at $0.50/M input and $1.50/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek-V3.2-Exp · 8 for GPT-3.5 Turbo
DeepSeek-V3.2-Exp outperforms in 1 benchmarks (GPQA), while GPT-3.5 Turbo is better at 0 benchmarks.
DeepSeek-V3.2-Exp 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, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 1.9x cheaper than GPT-3.5 Turbo ($0.50/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 3.7x cheaper than GPT-3.5 Turbo ($1.50/1M tokens).
In conclusion, GPT-3.5 Turbo is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. DeepSeek-V3.2-Exp can generate longer responses up to 65,536 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while GPT-3.5 Turbo uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while GPT-3.5 Turbo was released on 2023-03-21.
DeepSeek-V3.2-Exp is 31 months newer than GPT-3.5 Turbo.
Sep 29, 2025
11 months ago
2.5yr newerMar 21, 2023
3.5 years ago
Knowledge Cutoff
When training data ends
GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while DeepSeek-V3.2-Exp'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 DeepSeek-V3.2-Exp's cutoff date.
—
Sep 2021
Provider Availability
DeepSeek-V3.2-Exp is available from Novita. GPT-3.5 Turbo is available from Azure, OpenAI.
DeepSeek-V3.2-Exp
GPT-3.5 Turbo
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and GPT-3.5 Turbo side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Exp vs GPT-3.5 Turbo.