Claudio Greco

Member of Technical Staff at @RekaAILabs working on Large Multimodal Foundation Models and Multimodal Agents. PhD from @cimec_unitrento.

[Reka @RekaAILabs]

We just released PhysicalRealismBench-U — a benchmark for testing whether VLMs actually understand physics in programmatically generated videos, fully attributable.

This is an important step toward models that understand and generate physically realistic outputs.

Best result across 9 frontier models: 57.7% realism F1.

Read our blog post here: https://t.co/yOEyZ2CASA

Visit the benchmark: https://t.co/Z9gPr4CiYt

[Reka @RekaAILabs]

We are excited to join forces with @moonvalley and merge the teams!

Together, we are building multimodal models that reason about, simulate, and act in the physical world.

Read the full announcement: https://t.co/tPPFrgoO8H

Stay tuned for a few exciting updates about our work in the coming weeks.

[Reka @RekaAILabs]

Our models are now available on @OpenRouter 🧠🦾

Our brand new Edge, designed for the constraints of the physical world:
⚡️️Sub-second latency
📉 Optimized compute
🏗️ Production-ready reasoning
Deploy frontier intelligence closer to your data. Try it now: https://t.co/eJ2xywS72j

And also Flash 3
- Cost-efficient multimodal model that processes text (multilingual) & images
- 21B general-purpose reasoning LLM

[Reka @RekaAILabs]

We're going live on r/LocalLLaMA at 10am PST for our first ever AMA! Come with questions - we've got a lot to share

[Adina Yakup @AdinaYakup]

Impressive 7B multimodal vision language model 🔥
Available on @huggingface

👉https://t.co/QdpJe5Pss4

[Mikel Artetxe @artetxem]

Many VLMs look impressive in evals.

But when you try to deploy them, the tradeoffs show up fast: memory, latency, token cost, throughput.

We built Reka Edge to change that: frontier visual intelligence that's actually deployable.

And it doesn't sacrifice quality for speed. Best-in-class for its size across:
• Video & Image Understanding (VQA-V2, MLVU, MMVU)
• Object Detection & Grounding (RefCOCO)
• Tool Use (Mobile Actions)
• Reliability & Truthfulness (VideoHallucer)

It even approaches Gemini 3 Pro at a fraction of the cost!

[Reka @RekaAILabs]

Meet Reka Edge – Our next-generation vision language model for physical AI. Uses 3x fewer input tokens and achieves 65% faster throughput compared to leading 8B models. Image understanding, video analysis, object detection, and tool use.

Built for Action. Fast enough for production, deployable anywhere.

Read more: https://t.co/GcIqYv3ezu

[Reka @RekaAILabs]

New Reka community node for n8n is live 🚀

AI powered video clipping + image analysis inside your workflows.

Create short clips. Analyze visuals. Ask questions about images. No code required.

🔗 https://t.co/yKkbkbS41g

#AI #n8n #automation

[Reka @RekaAILabs]

Introducing Parallel Thinking for Reka Research!

Instead of one line of reasoning, we explore multiple paths in parallel, then resolve the best answer. Big accuracy gains on Research-Eval (+4.2) and SimpleQA (+3.5).

Now live in the Reka Research API!

[Mikel Artetxe @artetxem]

How Reka Speech does efficient timestamped transcription:

1. Encode audio with a 300M encoder → feed into a 500M backbone LM
2. During prefilling, offload the query/key embeddings to CPU (QK cache)
3. Generate transcript autoregressively (KV cache stays on GPU)
4. Pull the QK cache back to GPU, recompute attention, and run dynamic programming to align audio & text tokens

Saves GPU memory → Enables larger batch sizes → Higher throughput at scale!

[Reka @RekaAILabs]

Introducing Reka Speech: an efficient and accurate transcription & translation model. 🗣️

On modern GPUs (e.g. H100), it runs 8x–35x faster than existing solutions for batch processing.

[Reka @RekaAILabs]

This is Frank.

Frank is tired of intelligent apps just generating text. Don't be like Frank!

Your apps can now actively research, analyze multiple sources, and return verified, structured data.

💡 Why developers love Reka Research:
- Drop-in replacement for OpenAI (change 2 lines of code)
- Built-in structured outputs
- Full reasoning transparency, see exactly how conclusions were reached
- Location-aware search capabilities
- Fine-grained source control (allow/block specific domains)
- FREE API access to get started

🎯 We just published a complete tutorial with video walkthrough + GitHub repo. Perfect if you're building apps that need reliable, verifiable information beyond basic text generation.

Read more here: https://t.co/A8sISfU3ah

#RekaAI #AI #WebDev #Research #API #TechTutorial #developer

[Reka @RekaAILabs]

🚨 New benchmark release 🚨

We're introducing Research-Eval: a diverse, high-quality benchmark for evaluating search-augmented LLMs

👉 Blogpost: https://t.co/fLJonKsJ08

👉 Dataset + code: https://t.co/fJiySwgO4s

🧵 Here's why this matters:

[Reka @RekaAILabs]

Reka Research is finally in @poe_platform! Have a look!

[Reka @RekaAILabs]

Learn from our prompt experts how to improve your #AI prompt in this short video 👉 https://t.co/a973sRbjVm

[Reka @RekaAILabs]

🎉 Big news! We've raised $110M from new and existing investors, including @nvidia & @Snowflake

This funding reinforces our position at the forefront of AI innovation, with exciting releases like Reka Vision, Reka Research & Reka Flash 3.1

Read more 👇
https://t.co/OAsKVyMF9Y

[Reka @RekaAILabs]

Reka Research is our AI agent that scours the web to answer your toughest questions. Ready to unlock its full potential? Learn directly from the team who built it!

[Sharath Raparthy @sharathraparthy]

a quick recap on what we have released last week at @RekaAILabs -

> reka flash 3.1 (open-sourced) - post-trained with some cool RL tricks

> reka quant - a quantization library which achieves near lossless quantisation to 3.5bit. its opensourced :)

> reka research agent - outperforms the geminis, sonars, claudes and gpts. plus its cheaper (25$ per 1000 requests)

> reka vision agent - lets creators streamline their video production pipeline, enterprises search over millions of hours of video or billions of images with natural language prompts and many more

we have more exciting followups which we will release soonish.

ok, back to work now.

[Mikel Artetxe @artetxem]

What a week! Recap of everything we released:

⚡️Reka Flash 3.1⚡️: Open source 21B reasoning model
🗜️Reka Quant🗜️: Open source quantization library
🔎Reka Research🔎: Agentic search-augmented chat
👁️Reka Vision👁️: Visual understanding & search platform

More details in thread 👇

[Aitor Ormazabal @aormazabalo]

For our third day of releases we are open sourcing some of our building blocks! I'm particularly happy to be open-sourcing RekaQuant 🗜️, part of our internal quantization stack that I led last year. Short thread on our approach to quantization 🧵1/n