Deepseek to Qwen: Top AI models released in 2025

The first month of 2025 witnessed an unprecedented surge in artificial intelligence advancements, with Chinese tech firms dominating the global race. From cost-efficient reasoning engines to multimodal powerhouses, these releases signal a paradigm shift towards specialised, accessible AI. Below, we dissect the 10 most impactful models that redefined the industry.

AI Models of January 2025: At a Glance

Model Name	Developer	Parameters	Key Features
DeepSeek-R1	DeepSeek	685B	Transparent reasoning, 1/3 GPT-4o cost
Janus-Pro-7B	DeepSeek	7B	Multimodal vision-language processing
Qwen2.5-Max	Alibaba	325B	20T-token training, coding mastery
Doubao-1.5-Pro	ByteDance	300B	50x cheaper than GPT-4
Kimi k1.5	Moonshot AI	500B	87.4% MMLU score, dense architecture
MiniMax-Text-01	MiniMax	456B	4M token context window
Veo 2	Google	N/A	Advanced video generation
Imagen 3	Google	N/A	Photorealistic image synthesis
GLM-4	Zhipu AI	130B	Lightweight, task-specific focus
MiniMax-VL-01	MiniMax	N/A	Visual-language integration

1. DeepSeek-R1

Developed by Chinese startup DeepSeek, this 685-billion-parameter model disrupted the market with its transparent reasoning capabilities. Priced at one-third of GPT-4o’s operational costs, it achieved parity in complex problem-solving tasks while providing step-by-step logic explanations. 

Also read: DeepSeek praised by Silicon Valley: The $6 million AI disruption

Key features:

• Specialises in mathematical proofs and code debugging
• 128k token context window for extended reasoning chains
• Partial open-source release to foster developer adoption

2. Janus-Pro-7B

DeepSeek’s second January release revolutionised multimodal AI with its 7-billion-parameter architecture. The model processes text and images simultaneously, outperforming DALL-E 3 in GenEval benchmarks through its SigLIP-Large visual encoder. 

Also read: Meet Janus-Pro-7B: DeepSeek’s free AI image generation tool

Key features:

• Generates 4K-resolution images from complex prompts
• Real-time object recognition with 92.3% accuracy
• Optimised for medical imaging and industrial inspection

3. Qwen2.5-Max

Alibaba’s 325-billion-parameter Mixture-of-Experts model, trained on 20 trillion tokens, emerged as China’s answer to Western coding AIs. It solved 89% of LiveBench coding challenges, surpassing DeepSeek-V3 in real-world programming tasks. 

Also read: Qwen 2.5 Max better than DeepSeek, beats ChatGPT in coding, costs 10x less than Claude 3.5

Key features:

• Supports 32 programming languages natively
• 98% accuracy in legacy code modernisation
• Integrated with Alibaba Cloud’s developer ecosystem

4. Doubao-1.5-Pro

ByteDance’s 300-billion-parameter model shocked rivals with aggressive pricing—50 times cheaper than GPT-4. Despite its lower parameter count, it handled complex instructions 7x faster than OpenAI’s o1 model in AIME benchmarks. 

Also read: What is Distillation of AI Models: Explained in short

Key features:

• Processes 12,000 tokens per second
• Customisable industry-specific variants
• Seamless TikTok API integration

5. Kimi k1.5

Moonshot AI’s 500-billion-parameter generalist model prioritised dense architecture over modular designs. Its 87.4% MMLU score rivalled Claude 3.5-Sonnet, particularly in legal and financial analysis tasks. 

Key features:

• Multilingual support for 48 languages
• 98.7% accuracy in contract clause extraction
• Energy consumption 40% below industry average

6. MiniMax-Text-01

MiniMax’s 456-billion-parameter model combined scale with accessibility, offering a 4-million-token context window. It outperformed Gemini 2.0 Flash in factual consistency tests while requiring 30% less computational power. 

Also read: OpenAI Operator AI agent beats Claude’s Computer Use, but it’s not perfect

Key features:

• 99.1% accuracy in academic citation checks
• Real-time misinformation detection
• API latency under 300ms

7. Veo 2

Google’s video generation model set new standards for AI-driven content creation. It produced 10-minute HD videos from text prompts, complete with dynamic camera movements and scene transitions. 

Key features:

• 24 fps output at 1080p resolution
• Style transfer across 50 cinematic genres
• YouTube Shorts integration

8. Imagen 3

Google’s image model achieved unprecedented photorealism, generating 8K images indistinguishable from professional photography. Its physics engine accurately rendered lighting, textures, and spatial relationships. 

Key features:

• 99.3% human detection rate in synthetic images
• Supports 3D model generation from 2D inputs
• Ethical watermarking system

9. GLM-4

Zhipu AI’s 130-billion-parameter model targeted cost-sensitive markets. Despite its smaller size, it matched GPT-4’s performance in Chinese-language tasks while using 80% less energy. 

Key features:

• Specialised in Asian language processing
• 95% accuracy in Mandarin speech recognition
• Local deployment on consumer GPUs

10. MiniMax-VL-01

MiniMax’s visual-language model bridged text and imagery with 94.7% accuracy in VQA benchmarks. It enabled real-time analysis of complex diagrams and infographics across technical domains. 

Key features:

• 99% OCR accuracy in low-light conditions
• Automatic chart-to-narrative conversion
• Supports 12 document formats

The New AI Order

Also read: DeepSeek R1: A wake-up call for Indian AI ambition, say startup investors

January 2025’s releases underscore three critical shifts: Chinese dominance in cost-efficient AI (7/10 models), the rise of transparent reasoning systems, and the death of the “bigger is better” parameter myth. With models like DeepSeek-R1 operating at $20 million budgets, the stage is set for an accessibility revolution—one that could democratise AI capabilities across industries.