Best Open Source LLMs in 2026: We Reviewed 7 Models
Blog post from Fireworks AI
In 2026, a detailed comparison of the best open-source large language models (LLMs) available on Fireworks highlights their distinctive capabilities and ideal applications. Models like Kimi K2.5, Qwen3 VL 235B, and DeepSeek v3.2 stand out for different strengths, such as visual-to-code generation, deep visual comprehension, and elite mathematical reasoning, respectively. The review underscores the importance of choosing the right model to optimize inference costs, response latency, and user experience, as each model offers unique features and performance metrics, such as Kimi K2.5's multimodal capabilities or Qwen3 VL 235B's high MMLU score. The report also discusses the architectural efficiency of these models, many of which use Mixture-of-Experts (MoE) to activate only a portion of their parameters per token, and evaluates them on benchmarks like GSM8K and SWE-Bench. Fireworks AI provides a platform for deploying these models, offering various deployment options that cater to different production needs while handling the infrastructure requirements of running trillion-parameter models, thus enabling efficient scaling and integration into enterprise workflows.