Model Comparison

DeepSeek-R1-0528 vs GPT-3.5 Turbo

DeepSeek-R1-0528 significantly outperforms across most benchmarks. GPT-3.5 Turbo is 1.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-R1-0528 outperforms in 1 benchmarks (GPQA), while GPT-3.5 Turbo is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Wed Apr 22 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-3.5 Turbo costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) costs the same as GPT-3.5 Turbo ($0.50/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.4x more expensive than GPT-3.5 Turbo ($1.50/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than GPT-3.5 Turbo.*

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

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
OpenAI
GPT-3.5 Turbo
Input tokens$0.50
Output tokens$1.50
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

DeepSeek-R1-0528 accepts 131,072 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
OpenAI
GPT-3.5 Turbo
Input16,385 tokens
Output4,096 tokens
Wed Apr 22 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 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.

DeepSeek-R1-0528

MIT

Open weights

GPT-3.5 Turbo

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while GPT-3.5 Turbo was released on 2023-03-21.

DeepSeek-R1-0528 is 27 months newer than GPT-3.5 Turbo.

DeepSeek-R1-0528

May 28, 2025

10 months ago

2.2yr newer
GPT-3.5 Turbo

Mar 21, 2023

3.1 years ago

Knowledge Cutoff

When training data ends

GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while DeepSeek-R1-0528'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-R1-0528's cutoff date.

DeepSeek-R1-0528

—

GPT-3.5 Turbo

Sep 2021

Provider Availability

DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. GPT-3.5 Turbo is available from Azure, OpenAI.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

GPT-3.5 Turbo

azure logo
Azure
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M
openai logo
OpenAI
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Has open weights
Higher GPQA score (81.0% vs 30.8%)
OpenAI
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
OpenAI
GPT-3.5 Turbo

FAQ

Common questions about DeepSeek-R1-0528 vs GPT-3.5 Turbo

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and GPT-3.5 Turbo is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. GPT-3.5 Turbo scores DROP: 70.2%, MMLU: 69.8%, HumanEval: 68.0%, MGSM: 56.3%, MATH: 43.1%.
Both models cost $0.50 per million input tokens.
DeepSeek-R1-0528 supports 131K tokens and GPT-3.5 Turbo supports 16K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 16K), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and GPT-3.5 Turbo is developed by OpenAI.