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Llama 3.1 8B Instruct vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Llama 3.1 8B Instruct offers 6.1K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. Phi-4-multimodal-instruct supports multimodal inputs. Llama 3.1 8B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.1 8B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 61.3% across 18 benchmarks. It excels particularly in GSM-8K (CoT) (84.5%), ARC-C (83.4%), API-Bank (82.6%). It supports a 262K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.
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Microsoft
Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
6 months newer
Llama 3.1 8B Instruct
Meta
2024-07-23
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Pricing Comparison
Cost per million tokens (USD)
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Llama 3.1 8B Instruct
Input:$0.03
Output:$0.03($0.09 cheaper)
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10
Performance Metrics
Context window and performance specifications
Average performance across 33 common benchmarks
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Llama 3.1 8B Instruct
Average Score:33.4%(+0.7%)
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Phi-4-multimodal-instruct
Average Score:32.7%
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 8B Instruct
2023-12-31
Phi-4-multimodal-instruct
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 3.1 8B Instruct
9 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cerebras
Throughput: 2047 tok/s
Latency: 0.2ms
DeepInfra
Throughput: 118 tok/s
Latency: 0.5ms
Fireworks
Throughput: 292 tok/s
Latency: 0.5ms
Groq
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Llama 3.1 8B Instruct
Avg Score:33.4%(+0.7%)
Providers:9
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Phi-4-multimodal-instruct
Avg Score:32.7%
Providers:1