🧠 AI/ML Engineer 📹 YouTube: https://xitter.cf/t.co/AdBzHLggKb 🐙 GitHub: https://xitter.cf/t.co/5D67i6dB6W
Vienna, Austria
Joined April 2019
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Florian Dedov retweeted
🚨 CRITICAL: GitLab flaw (CVSS 10.0) affects 12 years of releases.
CVE-2026-110264 could allow unauthenticated remote code execution on self-managed servers.
Read - thehackernews.com/2026/10/cr…
Florian Dedov retweeted
Mistral has released new Speech models! Voxtral Small Transcribe 3 takes the #3 spot on the Artificial Analysis Speech to Text leaderboard, and Voxtral 3 TTS enters the top 12 in both Text to Speech arenas
@MistralAI has released Voxtral 3: a new Text to Speech model and three Speech to Text models (Small Transcribe 3, Mini Transcribe 3 and Mini Transcribe Realtime 3). We evaluated all of them.
Key takeaways:
➤ Speech to Text: Voxtral Small Transcribe 3 takes the #3 spot on the Artificial Analysis Speech to Text leaderboard with a 2.1% AA-WER Index, ahead of ElevenLabs Scribe v2 (2.2%) and Grok Voice Transcribe 2.0 (2.3%). Voxtral Mini Transcribe 3 lands at #5 with 2.2%.
➤ Streaming Speech to Text: Voxtral Mini Transcribe Realtime 3 scores 3.3% final-transcript AA-WER at the 960 ms setting (#6 of 46) and 3.6% at 480 ms, down from 5.2% for the previous Voxtral Mini Transcribe Realtime.
➤ Text to Speech, Provider Voice: Voxtral 3 TTS scores an Elo of 1,218 across 1,599 arena appearances, ranking #12 of 98, just behind Breeze TTS 2 at 1,221 and ahead of Inworld Realtime TTS-2 Flash and StepAudio 2.5 TTS at 1,216. It ranks #13 in English (US) and #12 in English (UK).
➤ Text to Speech, Controlled Voice: Voxtral 3 TTS scores 1,068 across 1,614 appearances, ranking #12 of 43 with the same 8 cloned voices, behind Eleven v3 at 1,072 and level with Ant Group's Ming-3.0-tts at 1,068. It ranks #10 in Assistants and #10 in English (UK).
➤ Pronunciation Robustness: Voxtral 3 TTS scores 84.4%, ranking #13 of 32 models, behind Qwen-Audio-3.1-TTS-Plus at 84.6% and ahead of HeyGen Voice at 83.2%. It ranks #3 in Standalone Terms at 93.9%.
➤ Pricing: Voxtral 3 TTS is priced at $13/1M characters, compared to Gemini 3.8 Flash TTS at $16.5/1M characters, Eleven v4 Turbo at $40/1M characters and Simba 3.2 at $6.6/1M characters.
See more details and listen to samples below ⬇️
Florian Dedov retweeted
Honest question:
What happened.
It used to be one global tech ecosystem online (esp in the west) trying to move technology forward. Push tech, opensource, decentralize power, enable the newcomers, use tech to move the world forward.
Now literally everything is about isolationist politics. You cant even celebrate a tech achievement anymore without bashing someone else.
No positivesum. Only zerosum.
Florian Dedov retweeted
I'd expand the moats left to:
- Proprietary data or content: data nobody else has, or unique content you can create
- Network effects / community: users make it more valuable for each other
- Audience / distribution: you can get attention on demand
- Physical component: hardware, locations, real-world operations
- Capital: owning assets and investing (esp into the AI companies as they are and will suck up large parts of the economy)
- Regulatory: licenses and legal barriers
Florian Dedov retweeted
Check out this nice overview of Delta from @NeuralNine, covering getting started, bringing others into your threads, reviewing changes, and more.
youtube.com/watch?v=lvK-IeQh…
Florian Dedov retweeted
Local Liquid d1 3B crushed OpenAI Decision at Snake 🐍
@liquidai d1 on a single RTX 3090 decides in 8 ms so its snake made 82 moves a second and ate 86 apples while OpenAI's API took 345 ms a call and ate 3
Run decision models -> atomic.chat
Today we release Open d1: two open-weight multimodal models in our d1 decision model family.
> d1-3B: text + vision
> d1-omni-600M: text + image or text + audio
> Real-time decision making anywhere, from data centers such as @nvidia DGX to RTX workstations to Jetson at the edge.
1/
Florian Dedov retweeted
72% of the intelligence with 3.8% of the GPUs.
Just to show how talented @MistralAI team is: this shows the "intelligence per GPU" ratio.
- Mistral 4: 3,800 Grace Blackwell (published) 🇫🇷
- GPT-6 Astra: 100,000+ Grace Blackwell (published)
- Grok 4.7: ~200,000 GPUs (estimate)
- Claude Opus 5.5: ~500,000 Trainium2 (estimate)
Proud!
Florian Dedov retweeted
France might still be losing to China.
But USA is losing to France.
Mistral has released Mistral Large 4, scoring 38 on the Artificial Analysis Intelligence Index; France is back to having the most intelligent model from outside the US and China
@MistralAI has released Mistral Large 4 in Research Public Preview, with plans to release the weights of the 1T parameter (49B active) model at the end of October. It achieves 38 on the Artificial Analysis Intelligence Index, comparable to GPT-6 Luna (max, 38) and DeepSeek V4.1 Flash (max, 39). It also achieves 50% on the Artificial Analysis Cyber Index, level with GLM-5.3-Flash and ahead of models such as Kimi K3 and DeepSeek V4.1 Flash (max).
Key benchmarking results for Mistral Large 4 Preview:
➤ Most intelligent model from outside the US and China: Mistral Large 4 Preview scores 38 on the Intelligence Index, comparable to DeepSeek V4.1 Flash (max, 39) and GPT-6 Luna (max, 38). This makes it the most intelligent model from outside the US and China, ahead of countries such as South Korea and the United Arab Emirates
➤ Level with GLM-5.3-Flash on cyber defense capability: Mistral Large 4 Preview scores 50 on the Artificial Analysis Cyber Index, level with GLM-5.3-Flash (50) and behind MiMo-V2.6-Pro (56). Once its weights are released, it will rank among the top three open weights models on the Cyber Index. Its strongest result is on CyberGym-E2E-AA, where it scores 82%, ahead of MiMo-V2.6-Pro (79%) and GPT-6 Luna (max, 78%)
➤ Over 4x the Cost per Task of similar-intelligence open weights models: Mistral Large 4 Preview costs $1.13 per Intelligence Index task with standard pricing of $1.36/$4.18 per 1M input/output tokens, with $0.14 per 1M cached input tokens. For the first two weeks, Mistral Large 4 Preview will be served at a 50% launch discount, bringing its Cost per Task down to $0.57. This is still more costly than GLM-5.3-Flash ($0.25) and DeepSeek V4.1 Flash (max, $0.27)
➤ Strong document and image reasoning: Mistral Large 4 Preview scores 19% on GDP.pdf, on par with MiMo-V2.6-Pro (19%) and behind Kimi K3 (22%). This is an 18-point improvement from Mistral Large 3, partly driven by improvements in their API, which now accepts 100 images per request, up from 8 for previous Mistral models
Key model details:
➤ Context Window: 512k tokens
➤ Multimodality: Text and image input, with text output
➤ Pricing: $1.36/$4.18 per 1M input/output tokens ($0.14 per 1M cached input tokens), with 50% off for the first two weeks ($0.68/$2.09)
➤ Availability: Research Public Preview on Mistral's API, with open weights planned for the end of October
Florian Dedov retweeted
FLUX 3 is the strongest world model in the world.
FLUX 3 is #1 on Physics-IQ, @GoogleDeepMind's benchmark for physical world understanding in video models.
How Physics-IQ works: given the start of a real filmed experiment, can a model predict what physically happens next? Tests span fluid dynamics, optics, solid mechanics, magnetism and thermodynamics, covering how liquids flow, light behaves and objects interact.
In most cases, we substantially outperform all other frontier models, Seedance 2.5, MiniMax H3, Gemini Omni 1.1 Flash, Veo 3.1 and Sora 2, Cosmos3.
The FLUX 3 base model outperforms all other foundation models, while FLUX 3 paired with a physics verification layer scores even higher.
The FLUX 3 backbone, with its strong physics understanding, gives FLUX 3 Action it’s strong action prediction for robotics, while also giving FLUX 3 Video physically accurate motion when you’re creating content, making ads, films and product shots.
Florian Dedov retweeted
"Europe only regulates AI."
Last 3 weeks: @ElevenLabs #1 in voice. @bfl_ml #1 in robotics. @MistralAI and @Aleph__Alpha shipping frontier open models.
🇪🇺 is building.
Florian Dedov retweeted
Small bird, fast wings, Kolibri is here.
78B parameters. 3.46B active. Up to 1M tokens of context. Built in Europe.
Now the weights are yours. Run it on your own hardware, under Apache 2.0.
Florian Dedov retweeted
Introducing GLM-5.3: Built to Code. Ready for Cyber Defense.
- Top-tier coding and agentic capabilities, achieved through post-training on the 743B base model
- A major leap in cybersecurity, setting a new standard among open models
Tech Blog: z.ai/blog/glm-5.3
