Grok 4.3 is xAI’s reasoning-focused Grok model for production API work where long context,
external tools, and structured answers matter. Explicitly recommends it as the replacement for
several older Grok 4 and Grok 3-era reasoning models, and says it delivers improved agentic
coding and web development capability.
Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts
routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers major
gains in agentic coding, front-end development, and overall reasoning, with a significantly improved “vibe coding”
experience. The model excels at complex tasks such as 3D scenes, games, and repository-level problem solving,
achieving a 78.8 score on SWE-bench Verified. It represents a substantial leap in both pure-text and multimodal
capabilities, performing at the level of leading state-of-the-art models.
Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and
a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed
visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.
Trivia
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear
attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety
of task evaluations, the 3.5 series consistently demonstrates performance on par with state-of-the-art leading
models. Compared to the 3 series, these models show a leap forward in both pure-text and multimodal capabilities.
NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum
compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer
Mixture-of-Experts architecture with multi-token prediction (MTP), it delivers over 50% higher token generation
compared to leading open models. The model features a 1M token context window for long-term agent coherence,
cross-document reasoning, and multi-step task planning. Latent MoE enables calling 4 experts for the inference
cost of only one, improving intelligence and generalization. Multi-environment RL training across 10+ environments
delivers leading accuracy on benchmarks including AIME 2025, TerminalBench, and SWE-Bench Verified. Fully open with
weights, datasets, and recipes under the NVIDIA Open License, Nemotron 3 Super allows easy customization and secure
deployment anywhere — from workstation to cloud.
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity
and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced
agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex
tasks across dynamic environments. Trained for production-grade performance, M2.7 handles workflows such
as live debugging, root cause analysis, financial modeling, and full document generation across Word,
Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on
Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems
operating in real-world digital workflows.
Roleplay, Science, Technology, Translation, Trivia
MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video,
and audio inputs within a unified architecture. It combines strong multimodal
perception with agentic capability - visual grounding, multi-step planning,
tool use, and code execution - making it well-suited for complex
real-world tasks that span modalities, 256K context window.
MiMo-V2-Pro is Xiaomi's flagship foundation model, featuring over 1T total
parameters and a 1M context length, deeply optimizesd for agentic scenarios.
It is highly adaptable to general agent frameworks like OpenClaw. It ranks
among the global top tier in the standard PinchBench and ClawBench benchmarks,
with perceived performance approaching that of Opus 4.6. MiMo-V2-Pro is designed
to serve as the brain of agent systems, orchestrating complex workflows, driving
production engineering tasks, and delivering results reliably.
GLM-5V-Turbo is Z.ai’s first native multimodasl agent foundation model, built for
vision-based coding and agent-driven tasks. It natively handles image, video, and
text inputs, excels at long-horizon planning, complex coding, and task execution,
and works seamlessly with agents to complete the full loop of “perceive → plan → execute“.