GPT-3.5 Turbo vs Llama 3.3 70B Instruct Comparison

Comparing GPT-3.5 Turbo and Llama 3.3 70B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

GPT-3.5 Turbo outperforms in 0 benchmarks, while Llama 3.3 70B Instruct is better at 5 benchmarks (GPQA, HumanEval, MATH, MGSM, MMLU).

Llama 3.3 70B Instruct significantly outperforms across most benchmarks.

Mon Mar 23 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.3 70B Instruct costs less

For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 2.5x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 7.5x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

In conclusion, GPT-3.5 Turbo is more expensive than Llama 3.3 70B Instruct.*

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

Lowest available price from all providers
Mon Mar 23 2026 • llm-stats.com
OpenAI
GPT-3.5 Turbo
Input tokens$0.50
Output tokens$1.50
Best providerAzure
Meta
Llama 3.3 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
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Context Window

Maximum input and output token capacity

Llama 3.3 70B Instruct accepts 128,000 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Llama 3.3 70B Instruct can generate longer responses up to 128,000 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.

OpenAI
GPT-3.5 Turbo
Input16,385 tokens
Output4,096 tokens
Meta
Llama 3.3 70B Instruct
Input128,000 tokens
Output128,000 tokens
Mon Mar 23 2026 • llm-stats.com

License

Usage and distribution terms

GPT-3.5 Turbo is licensed under a proprietary license, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.

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

GPT-3.5 Turbo

Proprietary

Closed source

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Release Timeline

When each model was launched

GPT-3.5 Turbo was released on 2023-03-21, while Llama 3.3 70B Instruct was released on 2024-12-06.

Llama 3.3 70B Instruct is 21 months newer than GPT-3.5 Turbo.

GPT-3.5 Turbo

Mar 21, 2023

3.0 years ago

Llama 3.3 70B Instruct

Dec 6, 2024

1.3 years ago

1.7yr newer

Knowledge Cutoff

When training data ends

GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while Llama 3.3 70B Instruct'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 Llama 3.3 70B Instruct's cutoff date.

GPT-3.5 Turbo

Sep 2021

Llama 3.3 70B Instruct

Provider Availability

GPT-3.5 Turbo is available from Azure, OpenAI. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks. The availability of providers can affect quality of the model and reliability.

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

Llama 3.3 70B Instruct

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.23/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $7.90/1M
sambanova logo
Sambanova
Input Price:Input: $0.60/1MOutput Price:Output: $1.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.70/1MOutput Price:Output: $0.80/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
together logo
Together
Input Price:Input: $0.88/1MOutput Price:Output: $0.88/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Larger context window (128,000 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (50.5% vs 30.8%)
Higher HumanEval score (88.4% vs 68.0%)
Higher MATH score (77.0% vs 43.1%)
Higher MGSM score (91.1% vs 56.3%)
Higher MMLU score (86.0% vs 69.8%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-3.5 Turbo
Meta
Llama 3.3 70B Instruct