Google Gemini 3.1 Ultra
Launched
2 million token context window. Native multimodal reasoning across text, image, audio, and video simultaneously. New sandboxed code execution tool. Improved grounding to cut hallucinations.
So what: You can now feed an entire codebase, hours of video, or massive documents into a single prompt. Multimodal means one model replaces separate image/audio/text pipelines.
Now what: Test for long-form content analysis workflows. Could power deep brand audits that ingest everything a client has in one pass.
Mar 20Google
Meta Llama 4 Maverick
Open Source
400B parameters, 128 experts (mixture-of-experts). 10 million token context — the longest available anywhere. Fully open-source, self-hostable.
So what: Free frontier-class model you can run without API costs. 10M context means you can feed it an entire business's worth of data.
Now what: Explore self-hosting for client projects where data privacy matters. Zero marginal cost for high-volume use cases.
Mar 2026MetaApache 2.0
Claude Opus 4.6 / Sonnet 4.6
Launched
1M token context. Opus leads SWE-bench for coding. Sonnet powers GitHub Copilot's coding agent. Sonnet leads GDPval-AA Elo benchmark (1,633 pts) for expert work.
So what: Best-in-class for code generation and agentic workflows. This is what's powering Claude Code right now.
Now what: Already using it. Keep leveraging for all builds. The agentic capability is why we can ship so fast.
CurrentAnthropic$5/M input (Opus)
OpenAI GPT-5.4 Pro
Launched
Tied with Gemini 3.1 Pro on intelligence benchmarks. $30/M input tokens. Available via ChatGPT Plus/Team/Pro.
So what: Competitive but expensive. 6x the cost of Gemini 3.1 Pro for similar performance.
Now what: Use for comparison testing only. Not cost-effective for production unless client specifically requests OpenAI.
Mar 5OpenAI$30/M input
Grok 4.20
Signal
Multi-agent architecture with 4 specialized agents. Profitable in Alpha Arena trading markets. Best-in-class for real-time factuality on current events. 500B "small" variant available.
So what: First model that's literally making money autonomously in trading. The multi-agent architecture is the direction everything is heading.
Now what: Watch for API access (expected Q2). The real-time factuality makes it interesting for news-based content generation.
Mar 22xAI
DeepSeek V3.2
Cheap
Near-frontier performance at $0.27/M input tokens — 10x cheaper than Claude Opus, 100x cheaper than GPT-5.4 Pro.
So what: Makes AI products viable at scale for any budget. Good enough for 80% of tasks at 10% of the cost.
Now what: Use for high-volume, lower-stakes tasks: content generation, data processing, first-pass analysis. Keep premium models for critical work.
CurrentDeepSeek$0.27/M input
Google Gemma 4
Open Source
Open-source models for reasoning and agentic workflows. Apache 2.0 license. 400M+ downloads, 100K+ community variants.
So what: Free, customizable models purpose-built for agents. The community ecosystem means pre-built fine-tunes for almost any vertical.
Now what: Check community variants for marketing/advertising-specific fine-tunes.
Apr 4GoogleApache 2.0
OpenAI Kills Sora
Dead
Video generation app shut down. Was burning $15M/day against lifetime revenue of $2.1M. Compute redirected to "Spud" (GPT-5.5).
So what: AI video generation hype >> actual revenue. The market isn't paying for standalone video gen tools yet. OpenAI is doubling down on language models instead.
Now what: Don't build standalone AI video products. Integrate video gen as a feature within larger workflows (like we're doing with Kling/Kie.ai).
Mar 24OpenAI
Microsoft MAI Models
Launched
Three new in-house models: MAI-Transcribe-1, MAI-Voice-1, MAI-Image-2. Available through Microsoft Foundry + MAI Playground.
So what: Microsoft building its own stack, reducing OpenAI dependency. Voice and transcription models could compete with Whisper/ElevenLabs.
Now what: Test MAI-Transcribe-1 against Whisper for our transcription pipeline. Could be cheaper/better.
Apr 2026Microsoft
Google TurboQuant
Infrastructure
Memory compression breakthrough. Reduces KV cache overhead using PolarQuant + Quantized JL compression. Makes massive context windows run efficiently.
So what: This is what makes 2M+ context windows practical. Without this, long-context models would be too expensive to run.
Now what: Background awareness only. This means long-context models will keep getting cheaper and faster.
Apr 4Google
MCP Crosses 97M Installs
Milestone
Anthropic's Model Context Protocol now the default standard for connecting AI agents to external tools and data. Every major AI provider ships MCP-compatible tooling.
So what: MCP is the USB port for AI. Building MCP-compatible tools/integrations = building for the entire AI ecosystem at once.
Now what: Any tool we build should be MCP-compatible. This is how our platform connects to the broader AI world.
Mar 2026Anthropic
Apple Siri Opens to 3rd-Party AI
Signal
iOS 27 will allow third-party AI models to power Siri. Claude, Gemini, GPT could all run natively as your phone assistant.
So what: The walled garden is opening. AI-powered services become accessible through the most intimate device people own.
Now what: Watch for developer APIs. Voice-first AI experiences on iPhone could be a major channel.
Mar 2026Apple