Background
On May 26, 2026, the easy-learn-ai model database received a large-scale expansion. The newly added and updated models reflect several key battlegrounds in the current AI industry competition.
DeepSeek-V4-Pro: The Open-Source Flagship
- 1.6 trillion total parameters, 49B activated via MoE (Mixture of Experts) architecture — only a small subset of experts is activated per request, balancing capacity and cost.
- Fully open source: unlike the closed GPT-5.5 and Claude 4.6, it can be downloaded, run locally, modified, and distilled — attractive for enterprises that cannot send data to third-party clouds.
- Supports both Thinking and Non-Thinking modes, letting users switch between deep reasoning and fast responses based on task complexity.
- 1,050K token context window — roughly 1.5 million Chinese characters or three full-length novels. Entire codebases, a full year of financial reports, or whole novels can be analyzed in one pass with cross-chapter reasoning.
- A "pro" variant openly warns that some requests may take minutes — a sign of AI products maturing by trading speed for quality.
- GPT-5.2-Codex targets long-horizon agentic coding: multi-file, multi-step engineering tasks with iterative fixes.
- Marketed as Kimi's smartest model: a multimodal agent supporting text, image, and video input, with thinking/non-thinking modes and tool calling.
- Key agent strengths: long-horizon code writing, instruction following, self-correction, and complex software engineering tasks.
- 256K context window, and open source.
- First stable release of the Gemini 3.5 series (May 19). Despite being a "Flash" model, it outperforms Gemini 3.1 Pro on multiple benchmarks.
- 1,048K input tokens, 65,536 output tokens, multimodal input (image, video, audio, PDF). Positioned for high-concurrency agents, code loops, RAG Q&A, and multimodal document understanding.
- GPT Image 2 (OpenAI): fast, high-quality generation, flexible sizes, high-fidelity image input — aimed at branding, product shots, ads, and complex editing.
- Nano Banana 2 (aka Gemini 3.1 Flash Image, Google): combines Nano Banana Pro's world knowledge and reasoning with Flash speed. Highlights precise text rendering (readable, correctly spelled) and output from 512px to 4K — targeting posters, infographics, and marketing assets.
- From ByteDance's Seed team: a unified multimodal audio-video joint generation architecture accepting text, image, audio, and video inputs (up to 9 images, 3 videos, 3 audio clips) plus natural-language instructions, producing 15-second multi-shot audio-video output.
- Improvements over v1.5: complex interaction/motion usability, physical accuracy, realism, and controllability.
GPT-5.5: OpenAI's Long-Memory Monster
Kimi K2.6: Moonshot AI's Agent Ambitions
Gemini 3.5 Flash: Google's Speed Play
Image Generation: GPT Image 2 vs Nano Banana 2
Seedance 2.0: Multimodal Video Generation
Key Observations
1. Context length is the new arms race (256K → 1,050K), changing interaction from incremental feeding to one-shot bulk input. 2. Open-source models are closing the quality gap with closed ones, giving enterprises real choice. 3. Dual thinking/non-thinking modes are becoming standard — no more paying a compute tax for simple tasks or settling for hasty answers on hard ones. 4. Multimodality has shifted from bonus to requirement — new text-only models are increasingly rare.
The author frames model competition as evolving from "who has the most parameters" (1.0), to "who excels in specific scenarios" (2.0), and eventually to "who embeds most naturally into human workflows" (3.0) — with these releases marking the transition from 1.0 to 2.0.
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Source commits: 9ead1f8 + b99eda0 (easy-learn-ai model database update)