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by Black Forest Labs
Black Forest Labs FLUX.1 [dev] with LoRA adapter support. This variant enables fine-tuned generation with custom trained LoRA weights for specialized styles, characters, or concepts. Based on the full 12B parameter FLUX.1 [dev] model with all its capabilities including high-resolution generation, accurate text rendering, and detailed composition. Perfect for custom workflows and specialized image generation tasks.
Black Forest Labs FLUX.1 [dev] is a cutting-edge 12 billion parameter rectified flow transformer for text-to-image generation. Second only to FLUX.1 [pro] with strong prompt following matching closed-source alternatives. Features guidance distillation for efficient inference, high-resolution generation (1024x1024), accurate text rendering, and detailed composition. Supports both text-to-image and image-to-image generation. Open weights enable scientific research and innovative workflows.
Black Forest Labs FLUX.2 [dev] is the latest generation text-to-image model with significant improvements over FLUX.1. Features enhanced prompt following, superior image quality, and faster generation. Built on the proven rectified flow transformer architecture with optimizations for better detail, composition, and text rendering. Excellent for creative workflows, concept art, and high-quality image generation with both text-to-image and image-to-image capabilities.
Black Forest Labs FLUX.1 [schnell] is the fastest variant of the FLUX.1 family, optimized for rapid text-to-image generation with fewer inference steps. Built on the same 12B parameter rectified flow transformer architecture as FLUX.1 [dev] but distilled for maximum speed. Generates high-quality 1024x1024 images in 1-4 steps compared to 20-50 steps for standard models. Ideal for real-time applications, interactive tools, and high-throughput image generation scenarios. Apache 2.0 licensed for unrestricted use including commercial applications.
Black Forest Labs FLUX.2 [klein] 4B is a lightweight, fast image generation model optimized for speed and efficiency. With 4 billion parameters, it delivers quick image generation while maintaining good quality. Perfect for rapid prototyping, bulk generation, and applications requiring low latency. Supports both text-to-image and image-to-image generation with excellent cost-efficiency.
Black Forest Labs FLUX.2 [klein] 9B is a balanced image generation model offering excellent quality-to-speed ratio. With 9 billion parameters, it provides better detail and composition than the 4B variant while remaining faster than full-size models. Ideal for production workloads requiring a balance between quality, speed, and cost. Supports both text-to-image and image-to-image generation.
by Mistral
Devstral 2 123B is Mistral AI's flagship agentic coding model, featuring 123B parameters optimized for software engineering tasks. Achieves 72.2% on SWE-bench Verified and 61.3% on SWE-bench Multilingual. Excels at codebase exploration, multi-file editing, and agentic workflows with tool use. Supports 200K context window with enhanced function calling and structured output. Designed for IDE integration via Mistral Vibe CLI. Released under modified MIT license for unrestricted commercial use.
by Deepseek
DeepSeek V3.1 is an optimized variant of DeepSeek V3 with enhanced chat capabilities. Offers excellent cost-efficiency with 685B MoE architecture and improved response quality for conversational tasks.
by Meta
Meta Llama 3.1 8B Instruct is an efficient multilingual instruction-tuned model optimized for dialogue and assistant use cases. With 8 billion parameters and 128K context length, it provides strong performance across general tasks, code generation, and multilingual understanding. Supports function calling and tool use with Grouped-Query Attention architecture. Ideal for deployment scenarios requiring lower compute resources while maintaining quality across English and 7 additional languages including German, French, Spanish, and Hindi.
Highly efficient DeepSeek flagship engineered for fast, capable reasoning and low-cost inference.
by ZAI
ZAI GLM 5.1 is a 744B parameter Mixture-of-Experts language model built with the GLM‑MoE DSA architecture. It excels at agentic engineering, achieving state-of-the-art performance on benchmarks such as HLE with tools (52.3), SWE‑Bench Pro (58.4) and AIME 2026 (95.3). The model supports extensive tool use and long‑horizon reasoning, with a large context window of up to 128K tokens. It is released under the MIT license.
DeepSeek R1 0528 is an upgraded 685B parameter reasoning model with significantly enhanced depth of reasoning and inference capabilities. Achieves 87.5% on AIME 2025 (up from 70%), 91.4% on AIME 2024, 73.3% on LiveCodeBench, and 1930 Codeforces rating. Features system prompt support, averages 23K thinking tokens per question for deeper analysis, and reduced hallucination rate. Released under MIT license supporting commercial use and distillation. Performance approaching O3 and Gemini 2.5 Pro levels.
Meta's flagship 405B parameter model representing the pinnacle of open-source AI. Exceptional reasoning and comprehensive knowledge for demanding applications.
by MiniMax
MiniMax M2.1 is a state-of-the-art MoE model with 230B total / 10B active parameters, optimized for agentic coding and complex multi-step workflows. Excels at multilingual programming, tool use, and long-horizon planning. Matches Claude Sonnet 4.5 on code benchmarks and exceeds it in multilingual scenarios. Features 196K context window with FP8 efficiency. Released under Modified-MIT license for commercial use.
DeepSeek V3.2 is the latest iteration of the DeepSeek V3 series with significant performance improvements. Features enhanced reasoning, coding capabilities, and better instruction following across diverse tasks.