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Llama 3.2 90B Instruct vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 3.6% higher average benchmark score. Llama 3.2 90B Instruct offers 224.0K more tokens in context window than Phi 4. Phi 4 is $0.54 cheaper per million tokens. Llama 3.2 90B Instruct supports multimodal inputs. Llama 3.2 90B Instruct is available on 5 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.2 90B was developed as a flagship-tier open-source model, designed to provide advanced capabilities with 90 billion parameters. Built to serve applications requiring high-quality reasoning and generation, it represents a powerful option within the Llama 3.2 series for demanding tasks.
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Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
2 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
Phi 4
Microsoft
2024-12-12
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Pricing Comparison
Cost per million tokens (USD)
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Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40
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Phi 4
Input:$0.07
Output:$0.14($0.54 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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Llama 3.2 90B Instruct
Average Score:71.9%
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Phi 4
Average Score:75.5%(+3.6%)
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Knowledge Cutoff
Training data recency comparison
Phi 4
2024-06-01
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 90B Instruct
5 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
DeepInfra
Throughput: 24 tok/s
Latency: 0.5ms
Fireworks
Throughput: 50 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 42 tok/s
Latency: 0.5ms
Together
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Llama 3.2 90B Instruct
Avg Score:71.9%
Providers:5
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Phi 4
Avg Score:75.5%(+3.6%)
Providers:1