Z.AI: GLM 4.5

Z.AI: GLM 4.5

GLM-4.5

GLM 4.5 is the latest flagship foundation model, purpose-built for agent-driven applications. Built on a Mixture-of-Experts (MoE) architecture, it supports context lengths of up to 128K tokens and offers major improvements in reasoning, code generation, and agent alignment. The model features a hybrid inference system with two modes: a “thinking mode” for complex reasoning and tool use, and a “non-thinking mode” for fast, real-time responses. Reasoning behavior can be easily managed with a simple boolean toggle.

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Creator zAI
Release Date July, 2025
License MIT
Context Window 131,072
Image Input Support No
Open Source (Weights) Yes
Parameters 355B, 32B active at inference time
Model Weights Click here

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Mistral: Mistral Medium 3.1

Mistral: Mistral Medium 3.1

Mistral-Medium-3.1

Mistral Medium 3.1 is an upgraded release of the Mistral Medium 3 model, built to deliver enterprise-grade performance with frontier-level capabilities at a fraction of the cost. Offering up to 8× lower operational expenses compared to traditional large models, it provides an ideal balance of advanced reasoning, multimodal performance, and scalability for professional and industrial applications.

The model performs strongly in coding, STEM reasoning, and enterprise adaptation, while supporting flexible deployment options including hybrid, on-premises, and in-VPC environments. Mistral Medium 3.1 achieves competitive accuracy against larger models such as Claude Sonnet 3.5/3.7, Llama 4 Maverick, and Command R+, all while maintaining broad cloud compatibility and seamless workflow integration.

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Creator MistralAI
Release Date August, 2025
License Proprietary
Context Window 131,072
Image Input Support Yes
Open Source (Weights) No
Input Cost $0.40/M tokens
Output Cost $2/M tokens

Reka Flash 3

Reka Flash 3

Reka-Flash-3

Reka Flash 3 is a 21B-parameter, instruction-tuned language model developed by Reka, designed for general-purpose use. It performs strongly in chat, coding, instruction following, and function calling. With a 32K context window and reinforcement learning optimization (RLOO), it delivers competitive performance to proprietary models while maintaining a smaller footprint. Optimized for low-latency and on-device deployment, it supports efficient quantization (as small as 11GB at 4-bit precision) and uses explicit <reasoning> tags to indicate its internal thought process.

Primarily an English-focused model with limited multilingual support, Reka Flash 3 is released under the Apache 2.0 license.

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Creator RekaAI
Release Date March, 2025
License Apache 2.0
Context Window 32,768
Image Input Support No
Open Source (Weights) Yes
Parameters 21B
Model Weights Click here

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MoonshotAI: Kimi Dev 72B

MoonshotAI: Kimi Dev 72B

Kimi-Dev-72B

Kimi Dev 72B is an open-source large language model fine-tuned for software engineering and issue resolution. Built on Qwen2.5-72B, it is trained with large-scale reinforcement learning that applies code patches to real repositories and validates them against full test suites—rewarding only correct and reliable solutions. The model achieves 60.4% on SWE-bench Verified, setting a new state-of-the-art benchmark among open-source models for code reasoning and automated bug fixing.

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Creator Moonshot AI
Release Date June, 2025
License Modified MIT License
Context Window 131,072
Image Input Support No
Open Source (Weights) Yes
Parameters 72.7B
Model Weights Click here

AI Chat Online

AI Chat Online

AI Chat is a free online platform that lets you interact with advanced AI chatbots for intelligent conversations, text generation, and image-based interactions. Experience fast, reliable, and engaging AI chat anytime.

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Anthropic: Claude Sonnet 4

Anthropic: Claude Sonnet 4

Claude-Sonnet-4

Claude Sonnet 4 builds on the strengths of Sonnet 3.7, delivering major improvements in coding and reasoning with greater precision and controllability. It achieves state-of-the-art results on SWE-bench (72.7%), striking an effective balance between advanced capability and computational efficiency.

Key upgrades include better autonomous codebase navigation, lower error rates in agent-driven workflows, and stronger reliability in handling complex instructions. Optimized for real-world use, Sonnet 4 offers advanced reasoning power while remaining efficient and responsive across a wide range of coding, software development, and general-purpose tasks.

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Creator Anthropic
Release Date May, 2025
License Proprietary
Context Window 1,000,000
Image Input Support Yes
Open Source (Weights) No
Input Cost $15/M tokens
Output Cost $75/M tokens

Qwen: Qwen3 235B A22B 2507

Qwen: Qwen3 235B A22B 2507

Qwen3-235B-A22B-2507

Qwen3 235B A22B 2507 Instruct is a multilingual, instruction-tuned Mixture-of-Experts model built on the Qwen3-235B architecture, activating 22B parameters per forward pass. It is optimized for versatile text generation tasks, including instruction following, logical reasoning, mathematics, coding, and tool use. The model supports a native 262K context window but does not include “thinking mode” (<think> blocks).

Compared to its base variant, this version offers substantial improvements in knowledge coverage, long-context reasoning, coding benchmarks, and open-ended alignment. It demonstrates particularly strong performance in multilingual understanding, mathematical reasoning (AIME, HMMT), and evaluation benchmarks such as Arena-Hard and WritingBench.

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Creator Alibaba
Release Date July, 2025
License Apache 2.0
Context Window 262,144
Image Input Support No
Open Source (Weights) Yes
Parameters 235B, 22.0B active at inference time
Model Weights Click here

Performance Benchmarks

Deepseek-V3-0324 GPT-4o-0327 Claude Opus 4 Non-thinking Kimi K2 Qwen3-235B-A22B Non-thinking Qwen3-235B-A22B-Instruct-2507
Knowledge
MMLU-Pro 81.2 79.8 86.6 81.1 75.2 83.0
MMLU-Redux 90.4 91.3 94.2 92.7 89.2 93.1
GPQA 68.4 66.9 74.9 75.1 62.9 77.5
SuperGPQA 57.3 51.0 56.5 57.2 48.2 62.6
SimpleQA 27.2 40.3 22.8 31.0 12.2 54.3
CSimpleQA 71.1 60.2 68.0 74.5 60.8 84.3
Reasoning
AIME25 46.6 26.7 33.9 49.5 24.7 70.3
HMMT25 27.5 7.9 15.9 38.8 10.0 55.4
ARC-AGI 9.0 8.8 30.3 13.3 4.3 41.8
ZebraLogic 83.4 52.6 89.0 37.7 95.0
LiveBench 20241125 66.9 63.7 74.6 76.4 62.5 75.4
Coding
LiveCodeBench v6 (25.02-25.05) 45.2 35.8 44.6 48.9 32.9 51.8
MultiPL-E 82.2 82.7 88.5 85.7 79.3 87.9
Aider-Polyglot 55.1 45.3 70.7 59.0 59.6 57.3
Alignment
IFEval 82.3 83.9 87.4 89.8 83.2 88.7
Arena-Hard v2* 45.6 61.9 51.5 66.1 52.0 79.2
Creative Writing v3 81.6 84.9 83.8 88.1 80.4 87.5
WritingBench 74.5 75.5 79.2 86.2 77.0 85.2
Agent
BFCL-v3 64.7 66.5 60.1 65.2 68.0 70.9
TAU1-Retail 49.6 60.3# 81.4 70.7 65.2 71.3
TAU1-Airline 32.0 42.8# 59.6 53.5 32.0 44.0
TAU2-Retail 71.1 66.7# 75.5 70.6 64.9 74.6
TAU2-Airline 36.0 42.0# 55.5 56.5 36.0 50.0
TAU2-Telecom 34.0 29.8# 45.2 65.8 24.6 32.5
Multilingualism
MultiIF 66.5 70.4 76.2 70.2 77.5
MMLU-ProX 75.8 76.2 74.5 73.2 79.4
INCLUDE 80.1 82.1 76.9 75.6 79.5
PolyMATH 32.2 25.5 30.0 44.8 27.0 50.2

Anthropic: Claude Opus 4.1

Anthropic: Claude Opus 4.1

Claude-Opus-4.1

Claude Opus 4.1 is the latest upgrade to Anthropic’s flagship model, delivering stronger performance in coding, reasoning, and agentic workflows. It reaches 74.5% on SWE-bench Verified and introduces major improvements in multi-file code refactoring, debugging accuracy, and fine-grained reasoning.

With extended thinking support up to 64K tokens, Opus 4.1 is well-suited for research, data analysis, and complex tool-assisted reasoning tasks, making it a powerful choice for advanced development and problem-solving.

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Creator Anthropic
Release Date August, 2025
License Proprietary
Context Window 200,000
Image Input Support Yes
Open Source (Weights) No
Input Cost $3/M tokens
Output Cost $15/M tokens

xAI: Grok Code Fast 1

xAI: Grok Code Fast 1

Grok-Code-Fast-1

Grok Code Fast 1 is a fast, cost-efficient reasoning model optimized for agentic coding. It provides visible reasoning traces within responses, enabling developers to guide and refine workflows for higher-quality outcomes.

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Creator xAI
Release Date August, 2025
License Proprietary
Context Window 256,000
Image Input Support No
Open Source (Weights) No
Input Cost $0.20/M tokens
Output Cost $1.50/M tokens

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