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Phi-4-multimodal-instruct vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 16.3% higher average benchmark score. Qwen3-235B-A22B-Thinking-2507 offers 131.1K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $3.15 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Overall, Qwen3-235B-A22B-Thinking-2507 is the stronger choice for coding tasks.
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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.
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Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME 2025 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
5 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
Pricing Comparison
Cost per million tokens (USD)
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($3.15 cheaper)
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:
Performance Metrics
Context window and performance specifications
Average performance across 40 common benchmarks
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Phi-4-multimodal-instruct
Average Score:27.0%
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Qwen3-235B-A22B-Thinking-2507
Average Score:43.3%(+16.3%)
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Knowledge Cutoff
Training data recency comparison
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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Phi-4-multimodal-instruct
1 providers
DeepInfra
Throughput: 25 tok/s
Latency: 0.5ms
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Qwen3-235B-A22B-Thinking-2507
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Phi-4-multimodal-instruct
Avg Score:27.0%
Providers:1
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Qwen3-235B-A22B-Thinking-2507
Avg Score:43.3%(+16.3%)
Providers:1