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Llama 3.2 3B Instruct vs o4-mini
Comprehensive side-by-side LLM comparison
o4-mini leads with 48.6% higher average benchmark score. o4-mini offers 44.0K more tokens in context window than Llama 3.2 3B Instruct. Llama 3.2 3B Instruct is $5.47 cheaper per million tokens. o4-mini supports multimodal inputs. Overall, o4-mini is the stronger choice for coding tasks.
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Meta
Llama 3.2 3B was created as an ultra-compact open-source model, designed to enable on-device and edge deployment scenarios. Built with just 3 billion parameters while retaining instruction-following abilities, it brings Meta's language technology to mobile devices, IoT applications, and resource-constrained environments.
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OpenAI
o4-mini was created as part of the next generation of OpenAI's reasoning models, designed to continue advancing the balance between analytical capability and operational efficiency. Built to bring cutting-edge reasoning techniques to applications requiring quick turnaround, it represents the evolution of compact reasoning-focused models.
6 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
o4-mini
OpenAI
2025-04-16
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Pricing Comparison
Cost per million tokens (USD)
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Llama 3.2 3B Instruct
Input:$0.01
Output:$0.02($5.47 cheaper)
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o4-mini
Input:$1.10
Output:$4.40
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Llama 3.2 3B Instruct
Average Score:32.8%
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o4-mini
Average Score:81.4%(+48.6%)
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Llama 3.2 3B Instruct
1 providers
DeepInfra
Throughput: 171.5 tok/s
Latency: 0.24ms
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o4-mini
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Llama 3.2 3B Instruct
Avg Score:32.8%
Providers:1
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o4-mini
Avg Score:81.4%(+48.6%)
Providers:1