Modeller

Google's fastest and most cost-effective Gemini 3.5-class model, delivering around 350 output tokens per second per the Artificial Analysis Index. Designed for low-latency and high-throughput agentic workflows such as agentic search and document processing, with configurable thinking levels, built-in computer use, and full multimodal support across a 1M-token context window.

Anthropic's new state-of-the-art model, a thoughtful and proactive successor to Opus 4.8 that approaches Claude Fable 5's frontier intelligence at half the price. Delivers major gains in coding, agentic workflows, computer use, knowledge work, and scientific research, with strong self-verification and iteration, configurable effort settings, and Anthropic's best alignment and safety results to date. Also available in a Fast mode that runs around 2.5x the default speed.

Google DeepMind's workhorse Flash model that builds on Gemini 3.5 Flash with better coding, knowledge work, and multimodal performance while reducing output token usage by roughly 17% per the Artificial Analysis Index. Natively multimodal across text, image, audio, and video with a 1M-token context window, configurable thinking levels, and built-in computer use, tuned for scaling agentic workflows at a lower cost per output token.

Moonshot AI's flagship Kimi model for frontier intelligence, agentic coding, knowledge work, and deep reasoning. Kimi K3 supports a 1-million-token context window for long-running software engineering and research workflows.

Thinking Machines Lab's open-weights general-purpose multimodal Mixture-of-Experts model with 975B total parameters and 41B active parameters. Inkling accepts text, image, and audio inputs, produces text, and is designed for agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation.

Google DeepMind'in yeni bir temel üzerinde yeniden geliştirdiği amiral gemisi Gemini modeli; 2 milyon token bağlam penceresi ve en zor matematik, kodlama ve multimodal görevler için Deep Think reasoning modu sunar. Metin, görüntü, ses ve videoyu yerel olarak işler; akışlı fonksiyon çağırmayı ve güvenilir uzun bağlam kullanımını destekler.

The fast, low-cost tier of OpenAI's GPT-5.6 series, optimized for high-volume, latency-sensitive tasks such as classification, extraction, routing, and lightweight agentic steps. Approaches the larger GPT-5.6 tiers on many benchmarks while running several times faster at a fraction of the price.

Meta Superintelligence Labs' updated flagship, building on Muse Spark with stronger agentic reasoning, more reliable multi-agent orchestration, and improved multimodal understanding across voice, text, and image. Extends the context window and reduces latency and reasoning token usage while raising coding and tool-use accuracy. Powers Meta AI across its product ecosystem.

OpenAI GPT-5.6 serisinin amiral gemisi modeli; zorlu gerçek dünya görevlerinde güvenilirliği ve verimliliği artırırken kodlama, bilimsel akıl yürütme, uzun vadeli planlama ve agent iş akışlarını geliştirir. Maksimum reasoning-effort ayarı ve karmaşık çok adımlı çalışmalar için alt agent'lar başlatan ultra modunu ekler.

OpenAI GPT-5.6 serisinin dengeli modeli; en yüksek kalite düzeyinden bir miktar ödün verirken belirgin şekilde daha düşük gecikme ve maliyet sunar. Ayarlanabilir akıl yürütme derinliğiyle güçlü reasoning, kodlama ve agent tabanlı araç kullanımını korur. Bu nedenle ileri yeteneklere ihtiyaç duyan yüksek hacimli production iş yükleri için varsayılan seçenek olmaya uygundur.

xAI'nin bugüne kadarki en yetenekli modeli; kodlama, agent görevleri ve bilgi çalışması için geliştirilmiş, gerçek yazılım geliştirme araçlarıyla birlikte tasarlanmıştır. OpenAI uyumlu API üzerinden güncel bilgiye erişimi, genişletilmiş akıl yürütmeyi ve geniş bağlamda araç kullanımını destekler.

Anthropic'in en yetenekli Sonnet sınıfı modeli; ileri kodlama, agent ve profesyonel çalışma yeteneklerini orta segmente taşır ve daha düşük fiyatla Opus 4.8 arasındaki farkı azaltır. Seçilebilir reasoning derinliğiyle uyarlanabilir düşünmeyi, 1 milyon token bağlam penceresini ve metin, görüntü ve dosya girişlerini destekler. Kod adı Fennec'tir.

Google's medium-size open-weight model with 12 billion parameters from the Gemma 4 family. Encoder-free unified multimodal architecture that natively processes text, image, audio, and video inputs without dedicated encoders. Features a 256K context window and supports 140+ languages. First medium-sized model capable of natively ingesting audio. Suitable for local deployment on GPUs with 16GB VRAM.

MiniMax's frontier open-weight model with 1M-token context window, native multimodality (text, image, video), and strong coding capabilities. Built on MiniMax Sparse Attention (MSA) architecture, achieving 59% on SWE-Bench Pro with significantly improved efficiency at long context.

Anthropic'in en gelişmiş modeli; Opus 4.7'nin üzerine kodlama, agent yetenekleri, akıl yürütme ve bilgi çalışmasında daha güçlü performans ekler. Daha dürüst yanıtlar, daha verimli araç kullanımı, dinamik iş akışı desteği ve iyileştirilmiş uyum sunar.

Alibaba's multimodal variant in the Qwen 3.7 family, optimized for vision understanding and multimodal tasks. Ranked

Google's balanced model combining Gemini 3 Pro's reasoning capabilities with the Flash line's latency, efficiency, and cost. Features configurable thinking levels, multimodal function responses, and streaming function calling for complex agentic workflows.

Google DeepMind's balanced Gemini 3.5 model that pairs Pro-line reasoning quality with Flash-line latency and cost. Natively multimodal across text, image, audio, and video with a 1M-token context window, configurable thinking levels, and streaming function calling, tuned for high-throughput production workloads.

Google's most cost-efficient Gemini model optimized for high-volume, low-latency use cases. Delivers 2.5x faster time to first token versus Gemini 2.5 Flash with full multimodal support. Ideal for agentic tasks, data extraction, translation, and classification.

Alibaba's dense 27B parameter model that outperforms its own 397B MoE predecessor on agentic coding benchmarks. Strong multilingual and reasoning capabilities released under Apache 2.0.

Alibaba's efficient Mixture-of-Experts model with 35B total parameters and 3B active per token. Frontier-level agentic coding performance with 73.4% on SWE-bench Verified and 92.7 on AIME 2026. Released under Apache 2.0.

OpenAI's compact reasoning model optimized for coding, computer use, and subagent tasks. Approaches GPT-5.4 performance on several benchmarks while running more than 2x faster.

Meta Superintelligence Labs' first model, featuring advanced reasoning, multimodal understanding, and agentic capabilities. Processes voice, text, and image inputs with tool use and multi-agent orchestration. Powers Meta AI across its product ecosystem.

Alibaba's proprietary flagship model in the Qwen 3.6 family, targeting enterprise AI workflows with stronger agentic coding capability, visual coding support, and end-to-end enterprise engineering features.