GPT-4o mini vs Llama 3.2 3B Instruct
GPT-4o mini leads the LLM Stats Score 3.6 to -6.1. Llama 3.2 3B Instruct is 21.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-4o mini leads the overall LLM Stats Score 3.6 to -6.1, ranking #307 overall.
In the 4 individual benchmarks reported for both models, GPT-4o mini wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.2 3B Instruct is roughly 21.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4o mini
- overall performance matters — it scores 3.6 and ranks #307 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
Choose Llama 3.2 3B Instruct
- cost matters — it's about 21.0x cheaper per token
- you want the most recent training data — it shipped Sep 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
9 reported for GPT-4o mini · 15 for Llama 3.2 3B Instruct
GPT-4o mini outperforms in 4 benchmarks (GPQA, MATH, MGSM, MMLU), while Llama 3.2 3B Instruct is better at 0 benchmarks.
GPT-4o mini 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-4o mini ($0.15/1M tokens) is 15.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).
For output processing, GPT-4o mini ($0.60/1M tokens) is 30.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).
In conclusion, GPT-4o mini is more expensive than Llama 3.2 3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Llama 3.2 3B Instruct can generate longer responses up to 128,000 tokens, while GPT-4o mini is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4o mini supports multimodal inputs, whereas Llama 3.2 3B Instruct does not.
GPT-4o mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o mini
Llama 3.2 3B Instruct
License
Usage and distribution terms
GPT-4o mini is licensed under a proprietary license, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
GPT-4o mini was released on 2024-07-18, while Llama 3.2 3B Instruct was released on 2024-09-25.
Llama 3.2 3B Instruct is 2 months newer than GPT-4o mini.
Jul 18, 2024
2.2 years ago
Sep 25, 2024
2.0 years ago
2mo newerKnowledge Cutoff
When training data ends
GPT-4o mini has a documented knowledge cutoff of 2023-10-01, while Llama 3.2 3B Instruct's cutoff date is not specified.
We can confirm GPT-4o mini's training data extends to 2023-10-01, but cannot make a direct comparison without Llama 3.2 3B Instruct's cutoff date.
Oct 2023
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Provider Availability
GPT-4o mini is available from Azure. Llama 3.2 3B Instruct is available from DeepInfra.
GPT-4o mini
Llama 3.2 3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o mini and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o mini vs Llama 3.2 3B Instruct.