Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 31.2% higher average benchmark score. Kimi K2 0905 offers 262.1K more tokens in context window than Gemma 3 4B. Gemma 3 4B is $3.04 cheaper per million tokens. Gemma 3 4B supports multimodal inputs. Overall, Gemma 3 4B is the stronger choice for coding tasks.
Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K 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 Google's latest advancement in AI technology.
Moonshot AI
Kimi K2 0905 is a language model developed by Moonshot AI. This model demonstrates exceptional performance with an average score of 84.0% across 6 benchmarks. It excels particularly in HumanEval (94.5%), MMLU (90.2%), MATH (89.1%). It supports a 524K token context window for handling large documents. The model is available through 2 API providers. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
5 months newer
Gemma 3 4B
2025-03-12
Kimi K2 0905
Moonshot AI
2025-09-05
Cost per million tokens (USD)
Gemma 3 4B
Kimi K2 0905
Context window and performance specifications
Average performance across 28 common benchmarks
Gemma 3 4B
Kimi K2 0905
Gemma 3 4B
2024-08-01
Available providers and their performance metrics
Gemma 3 4B
DeepInfra
Kimi K2 0905
Gemma 3 4B
Kimi K2 0905
Gemma 3 4B
Kimi K2 0905
Novita
ZeroEval