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Kimi K2 vs Llama 4 Behemoth
Comprehensive side-by-side LLM comparison
Kimi K2 offers 60.1K more tokens in context window than Llama 4 Behemoth. Kimi K2 is $2.90 cheaper per million tokens. Llama 4 Behemoth supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Moonshot AI
Kimi K2, released by Moonshot AI on July 11, 2025, is an open-weight Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters per inference. It features a 256K token context window (expanded from 128K in an September 2025 update) and demonstrated strong performance on agentic coding benchmarks. Kimi K2 targets software engineering agents, tool-use workflows, and open-source deployments under a modified MIT license.
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Meta AI
Llama 4 Behemoth is a research-scale Mixture-of-Experts language model with approximately 2 trillion total parameters (288 billion active per inference), developed by Meta as a teacher model for the Llama 4 family. Available only in limited preview, it serves as the knowledge distillation source for Llama 4 Scout and Maverick. Behemoth targets research applications requiring the largest-scale open-weight model architecture from the Llama 4 generation.
Kimi K2
Moonshot AI
2025-07-11
Pricing Comparison
Cost per million tokens (USD)
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Kimi K2
Input:$0.60
Output:$2.50($2.90 cheaper)
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Llama 4 Behemoth
Input:$3.00
Output:$3.00
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Kimi K2
1 providers
Moonshot AI
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Llama 4 Behemoth
1 providers
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Kimi K2
Avg Score:0.0%
Providers:1
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1