Modeller

Tüm sağlayıcılardaki 56 kanonik LLM modelini inceleyin

Bazı açıklamalar otomatik çevrilmiş pilot içeriklerdir ve henüz editör tarafından incelenmemiştir.

56 modelden 49–56 arası gösteriliyor

Qwen3 Coder131K ctx

Alibaba's Qwen3 Coder model optimized for software development tasks including code generation, debugging, code review, and technical documentation with strong multilingual programming support.

DeepSeek R1131K ctx

Karmaşık ve çok adımlı görevler için pekiştirmeli öğrenmeyle eğitilmiş, akıl yürütme odaklı DeepSeek modeli. Özellikle sıralı reasoning gerektiren matematik, bilim ve kodlama görevlerinde güçlüdür.

Codestral256K ctx

Mistral AI's cutting-edge code generation model specializing in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code completion, correction, and test generation. Features efficient architecture with 2x faster generation than its predecessor.

ISSAI KazLLM 1.0 70B128K ctx

Large language model developed by ISSAI (Nazarbayev University) customized from Llama 3.1 70B to improve helpfulness of responses in the Kazakh language. Part of Kazakhstan's initiative to ensure the country benefits from generative AI advancements.

Llama 3.3 70B Instruct131K ctx

Meta's flagship open-weight model with 70 billion parameters. Strong multilingual capabilities with competitive performance on reasoning and coding benchmarks. Available for self-hosting and through various inference providers.

Command R7B128K ctx

Cohere's compact 7B parameter model optimized for RAG, tool use, and code tasks. Delivers top-tier speed and efficiency on commodity GPUs and edge devices with 128K context window.

DeepSeek V3128K ctx

DeepSeek's third-generation large language model featuring mixture-of-experts architecture, strong multilingual capabilities, and competitive performance on reasoning and coding benchmarks.

Llama 3.1 8B Instruct131K ctx

Meta's efficient open-weight model with 8 billion parameters from the Llama 3.1 family. Optimized for instruction following with strong performance on general tasks, coding, and multilingual benchmarks. Ideal for cost-effective deployment and edge inference scenarios.