DeepSeek-R1 vs GPT-3.5 Turbo
Comparing DeepSeek-R1 and GPT-3.5 Turbo across benchmarks, pricing, and capabilities.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-R1 and GPT-3.5 Turbo trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GPT-3.5 Turbo is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1 also accepts a larger context window (131,072 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-R1
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Jan 2025
- you need open weights you can self-host or fine-tune
Choose GPT-3.5 Turbo
- cost matters — it's about 1.3x cheaper per token
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 8 for GPT-3.5 Turbo
DeepSeek-R1 and GPT-3.5 Turbodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.1x more expensive than GPT-3.5 Turbo ($0.50/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 1.5x more expensive than GPT-3.5 Turbo ($1.50/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than GPT-3.5 Turbo.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
License
Usage and distribution terms
DeepSeek-R1 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-R1 was released on 2025-01-20, while GPT-3.5 Turbo was released on 2023-03-21.
DeepSeek-R1 is 22 months newer than GPT-3.5 Turbo.
Jan 20, 2025
1.7 years ago
1.8yr 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-R1'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-R1's cutoff date.
—
Sep 2021
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. GPT-3.5 Turbo is available from Azure, OpenAI.
DeepSeek-R1
GPT-3.5 Turbo
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and GPT-3.5 Turbo side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs GPT-3.5 Turbo.