📆 Open source just pulled up to Opus 4.6 — at 1/20th the price · ThursdAI - The top AI news from the past week summary

Key takeaways

Open source AI models are rapidly advancing, with GLM-5 and MiniMax 2.5 pushing boundaries in performance and efficiency.
Major companies like Google and OpenAI are intensifying their competition in the AI space, launching groundbreaking models that reshape industry standards.
SeeDance 2.0 exemplifies the cutting-edge capabilities of current AI in video generation, setting a new bar for realism and interactivity.
The integration of AI tools into daily work presents challenges, with many individuals feeling the stress of maintaining effectiveness while managing multiple AI-driven processes.

Summary

Open Source Breakthroughs: GLM-5 and MiniMax 2.5

This week's episode highlights two significant releases in the world of open-source AI, with Z.ai launching their GLM-5 model, boasting an impressive 744 billion parameters and achieving high scores on coding benchmarks. Lou from Z.ai discussed how the model significantly improves upon its predecessor (GLM-4.5) by increasing its parameter count, optimizing pre-training with a vast amount of tokens, and utilizing a new sparse attention mechanism to enhance performance on long context tasks. Minimax also joined the conversation, unveiling their M2.5 model, which achieved an 80.2% score on SWE-bench, showcasing rapid advancements in performance and cost-effectiveness compared to other models. Olive from Minimax emphasized their focus on efficient Reinforcement Learning practices, enabling competitive performance with lower operational costs.

Big Labs Make Big Moves: Gemini 3 and GPT 5.3

The episode continued with breaking news as Google unveiled their Gemini 3 Deep Think model, achieving a record high on the ArcAGI-2 benchmark at 84.6%. This release, along with humanity's last exam results suggesting groundbreaking advancements in AI reasoning capabilities, places Gemini firmly at the forefront of the space, challenging the likes of OpenAI’s models. OpenAI, not to be outdone, announced their GPT 5.3 Codex Spark, designed for real-time coding, boasting speeds of over 1000 tokens per second but with some trade-offs in intelligence. The discussions demonstrated a landscape where competition among these major labs is fierce and drives rapid innovation.

Advancements in AI Video Generation: SeeDance 2.0

A focal point of the podcast was ByteDance’s SeeDance 2.0, a revolutionary video generation model capable of producing detailed and synchronized multimedia outputs. The host and guests discussed its capabilities, including accepting multiple references for video, audio, and images to create cohesive cinematic experiences. The advancements in sound quality and physical realism showcased a leap in AI's ability to generate content that closely resembles real-life visuals and sounds, potentially altering the content creation landscape.

AI Culture: Balancing Innovation and Overwork

A recurring theme was the tension between the rapid advances in AI technology and the mental strain on individuals integrating these tools into their workflows. Guests expressed concerns about getting adequate sleep amidst the anxiety that their agents might not be performing optimally when left unattended. This underscores the importance of creating a balance between leveraging AI advancements and maintaining personal wellness, as the pressure to utilize these tools can lead to burnout.

Show notes

Hey dear subscriber, Alex here from W&B, let me catch you up!

This week started with Anthropic releasing /fast mode for Opus 4.6, continued with ByteDance reality-shattering video model called SeeDance 2.0, and then the open weights folks pulled up!

Z.ai releasing GLM-5, a 744B top ranking coder beast, and then today MiniMax dropping a heavily RL’d MiniMax M2.5, showing 80.2% on SWE-bench, nearly beating Opus 4.6! I’ve interviewed Lou from Z.AI and Olive from MiniMax on the show today back to back btw, very interesting conversations, starting after TL;DR!

So while the OpenSource models were catching up to frontier, OpenAI and Google both dropped breaking news (again, during the show), with Gemini 3 Deep Think shattering the ArcAGI 2 (84.6%) and Humanity’s Last Exam (48% w/o tools)... Just an absolute beast of a model update, and OpenAI launched their Cerebras collaboration, with GPT 5.3 Codex Spark, supposedly running at over 1000 tokens per second (but not as smart)

Also, crazy week for us at W&B as we scrambled to host GLM-5 at day of release, and are working on dropping Kimi K2.5 and MiniMax both on our inference service! As always, all show notes in the end, let’s DIVE IN!

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Open Source LLMs

Z.ai launches GLM-5 - #1 open-weights coder with 744B parameters (X, HF, W&B inference)

The breakaway open-source model of the week is undeniably GLM-5 from Z.ai (formerly known to many of us as Zhipu AI). We were honored to have Lou, the Head of DevRel at Z.ai, join us live on the show at 1:00 AM Shanghai time to break down this monster of a release.

GLM-5 is massive, not something you run at home (hey, that’s what W&B inference is for!) but it’s absolutely a model that’s worth thinking about if your company has on prem requirements and can’t share code with OpenAI or Anthropic.

They jumped from 355B in GLM4.5 and expanded their pre-training data to a whopping 28.5T tokens to get these results. But Lou explained that it’s not only about data, they adopted DeepSeeks sparse attention (DSA) to help preserve deep reasoning over long contexts (this one has 200K)

Lou summed up the generational leap from version 4.5 to 5 perfectly in four words: “Bigger, faster, better, and cheaper.” I dunno about faster, this may be one of those models that you hand off more difficult tasks to, but definitely cheaper, with $1 input/$3.20 output per 1M tokens on W&B!

While the evaluations are ongoing, the one interesting tid-bit from Artificial Analysis was, this model scores the lowest on their hallucination rate bench!

Think about this for a second, this model is neck-in-neck with Opus 4.5, and if Anthropic didn’t release Opus 4.6 just last week, this would be an open weights model that rivals Opus! One of the best models the western foundational labs with all their investments has out there. Absolutely insane times.

MiniMax drops M2.5 - 80.2% on SWE-bench verified with just 10B active parameters (X, Blog)

Just as we wrapped up our conversation with Lou, MiniMax dropped their release (though not weights yet, we’re waiting ⏰) and then Olive Song, a senior RL researcher on the team, joined the pod, and she was an absolute wealth of knowledge!

Olive shared that they achieved an unbelievable 80.2% on SWE-Bench Verified. Digest this for a second: a 10B active parameter open-source model is directly trading blows with Claude Opus 4.6 (80.8%) on the one of the hardest real-world software engineering benchmark we currently have. While being alex checks notes ... 20X cheaper and much faster to run? Apparently their fast version gets up to 100 tokens/s.

Olive shared the “not so secret” sauce behind this punch-above-its-weight performance. The massive leap in intelligence comes entirely from their highly decoupled Reinforcement Learning framework called “Forge.” They heavily optimized not just for correct answers, but for the end-to-end time of task performing. In the era of bloated reasoning models that spit out ten thousand “thinking” tokens before writing a line of code, MiniMax trained their model across thousands of diverse environments to use fewer tools, think more efficiently, and execute plans faster. As Olive noted, less time waiting and fewer tools called means less money spent by the user. (as confirmed by @swyx at the Windsurf leaderboard, developers often prefer fast but good enough models)

I really enjoyed the interview with Olive, really recommend you listen to the whole conversation starting at 00:26:15. Kudos MiniMax on the release (and I’ll keep you updated when we add this model to our inference service)

Big Labs and breaking news

There’s a reason the show is called ThursdAI, and today this reason is more clear than ever, AI biggest updates happen on a Thursday, often live during the show. This happened 2 times last week and 3 times today, first with MiniMax and then with both Google and OpenAI!

Google previews Gemini 3 Deep Think, top reasoning intelligence SOTA Arc AGI 2 at 84% & SOTA HLE 48.4% (X , Blog)

I literally went🤯 when Yam brought this breaking news. 84% on the ARC-AGI-2 benchmark. For context, the highest score prior to this was 68% from Opus 4.6 just last week. A jump from 68 to 84 on one of the hardest reasoning benchmarks we have is mind-bending. It also scored a 48.4% on Humanity’s Last Exam without any tools.

Only available to Ultra subscribers to Gemini (not in API yet?) this model seem to be the current leader in reasoning about hard problems and is not meant for day to day chat users like you and me (though I did use it, and it’s pretty good at writing!)

They posted Gold-medal performance on 2025 Physics and Chemistry Olympiads, and an insane 3455 ELO rating at CodeForces, placing it within the top 10 best competitive programmers. We’re just all moving so fast I’m worried about whiplash! But hey, this is why we’re here, we stay up to date so you don’t have to.

OpenAI & Anthropic fast modes

Not 20 minutes passed since the above news, when OpenAI announced a new model that works only for Pro tier members (I’m starting to notice a pattern here 😡), GPT 5.3 Codex Spark.

You may be confused, didn’t we just get GPT 5.3 Codex last week? well yeah, but this one, this one is its little and super speedy brother, hosted by the Cerebras partnership they announced a while ago, which means, this coding model absolutely slaps at over 1000t/s.

Yes, over 1K tokens per second can be generated with this one, though there are limits. It’s not as smart, it’s text only, it has 128K context, but still, for MANY subagents, this model is an absolute beast. It won’t refactor in one shot your whole code-base but it’ll generate and iterate on it, very very quick!

OpenAI also previously updated Deep Research with GPT 5.2 series of models, and we can all say bye bye to the “older” version of models, like 5, o3 and most importantly GPT 4o, which got a LOT of people upset (enough that they have a hashtag going, #keep4o) !

Anthropic also announced their fast mode (using /fast) in Claude Code btw on Saturday, and that one is absolutely out of the scope for many users, with $225/1M tokens on output, this model will just burn through your wallet. Unlike the Spark version, this seems to be the full Opus 4.6 just... running on some dedicated hardware? I thought this was a rebranded Sonnet 5 at first but Anthropic folks confirmed that it wasn’t.

Vision & Video

ByteDance’s Seedance 2.0 Shatters Reality (and nobody in the US can use it)

I told the panel during the show: my brain is fundamentally broken after watching the outputs from ByteDance’s new Seedance 2.0 model. If your social feed isn’t already flooded with these videos, it will be so very soon (supposedly the API launches Feb 14 on Valentines Day)

We’ve seen good video models before. Sora blew our minds and then Sora 2, Veo is (still) great, Kling was fantastic. But Seedance 2.0 is an entirely different paradigm. It is a unified multi…

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📆 Open source just pulled up to Opus 4.6 — at 1/20th the price