🚀🤖 Mistral’s New AI Crushes GPT-4o & Claude 3.7 — And Costs Less Than DeepSeek! 💥💸 | AI Revolution - video Dailymotion

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Mistral has just launched a groundbreaking AI model that outperforms GPT-4o and Claude 3.7, delivering superior results at a fraction of the cost of DeepSeek! 🧠🔥 This new powerhouse is shaking up the AI landscape, making cutting-edge technology more affordable and accessible than ever. 🌍✨  Discover how Mistral is redefining AI performance and value in today’s competitive tech world! ⚡🤖  #MistralAI #GPT4o #Claude37 #AIInnovation #TechBreakthrough #ArtificialIntelligence #AIModel #DeepSeek #AIPerformance #AffordableAI #NextGenAI #MachineLearning #AIRevolution #TechNews #AICompetition #FutureTech #AI2025 #SmartTech #DigitalTransformation #Innovation

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00:00Mistral just launched Medium 3, a frontier-class AI model that outperforms GPT-40 and Claude 3.7

00:10Sonnet in coding, languages, and even multimodal tasks while costing a fraction to run. It hits

00:16over 90% of Claude's performance for just $0.40 per million input tokens and runs smoothly on

00:23only four GPUs. And now that it powers LayChat Enterprise with deep integrations, privacy-first

00:29architecture, and no-code AI agents, OpenAI finally has a serious competitor coming straight out of

00:36Europe. The catchphrase Mistral's own research blog led with is, Medium is the new large, and the

00:42company is leaning into that pretty hard. Medium 3 sits between their featherweight small and whatever

00:49large. Surprise, they're teasing for later. But don't let the name fool you. Internally, it's what

00:55they call a frontier-class model. It delivers performance that lands in the same neighborhood

00:59as Anthropics Claude 3.7 Sonnet, Cohere's Command-A, Meta's Llama 4 Maverick, and even OpenAI's

01:07freshly announced GPT-40, while pulling that off on a much skinnier compute diet. In plain English,

01:13you can wedge this thing into a four GPU on-prem rig or spin it up in a cloud VPC and still crank out

01:21results that would usually demand far chunkier hardware. Now the headline number that made everyone

01:26raise an eyebrow is the cost. Benchmarks show Medium 3 reaches more than 90% of Claude Sonnet's

01:32overall benchmark score. Yet Mistral quotes just $0.40 per million input tokens and $20.80 per million

01:40output tokens when you hit their API. For comparison, Sonnet is listed at $3 per million

01:46input and $15 per million output. Some of Mistral's own research material even shows an alternative

01:52rate card of $2 per million output. So the exact figure depends on which skew or deployment path you

01:58pick, but either way you're staring at something in the neighborhood of an 8x price cut. That's wild

02:04in a market where model bills blow up faster than GPU stock on launch day. Performance claims

02:10always need receipts and Mistral came armed. On Human Eval and MultiPLE, the two coding benchmarks

02:16everyone loves to quote Medium 3 matches or beats Claude Sonnet and GPT-40. Third-party human

02:23evaluations from Surge show it winning 82% of coding scenarios against Llama 4 Maverick and nearly 70%

02:31against Cohere Command A. It's not just about code either. Costs multilingual tasks at it and you get

02:37higher win rates over Llama 4 Maverick in English 67%, French 71%, Spanish 73%, and Arabic 65%. On multimodal

02:49reasoning, numbers like 0.953 on Dock VQA, 0.937 on AI2D, and 0.826 on Chart QA pop up impressive because

03:02multimodal is still where many mid-sized models all that horsepower turns out to be especially handy

03:09for STEM workloads. Medium 3 doesn't lock up while chewing on giant math proofs or engineering docs,

03:15and it compiles code fast enough that dev teams in finance, energy, and healthcare have already

03:20plugged data versions into production pipelines. A couple of those early testers are reportedly letting

03:25the model pre-trained continuously on proprietary data than fine-tuning in quick bursts when requirements

03:31shift, effectively running an in-house feedback loop without the headache of starting from scratch

03:36every time. That adapt-as-you-go angle is part of Mistral's pitch. Don't pick between black box

03:43SaaS fine-tuning or a DIY deployment, just blend both. Money matters too, and Medium 3 isn't only cheap

03:51compared to Anthropics lineup. It also beats DeepSeq V3, which until now enjoyed the reputation of being

03:58the cost-efficiency champ. That allows small teams to kick the tires through the API, then graduate to

04:04a self-hosted image when the CFO starts breathing down their neck about data residency or vendor lock-in.

04:10Astral even calls Medium 3 a proprietary model, so no MIT-style license, but they've kept everything

04:17flexible. Throw it in Mistral LaPlatefmum, light it up on Amazon SageMaker, or wait a few weeks for

04:23IBM Watson X, NVIDIA NIM, Azure AI Foundry, and Google Cloud Vertex integrations to go live. Whichever

04:30route you choose, the company insists, you'll still be able to slide their weights onto your own GPU stack

04:37if you want total control. The under-the-hood strategy is all about hybrid deployments. You can keep

04:44inference in a private subnet, slam a low-latency tenant in a public region for burst traffic,

04:50or fork the entire thing and run it fully on-prem. Because we're talking about a French firm operating

04:56under GDPR and soon the EU AI Act, data governance boxes get ticked pretty aggressively. Audit logs,

05:06fine-grained ACLs, memory-based personalization, and the ability to unplug from the cloud completely

05:12all come baked into the architecture. That's gold for banks, hospitals, and utilities who live and die

05:18by regulations. And that credibility boost lands at the perfect moment because Medium 3 is already the

05:25motor under Le Chat Enterprise, the customer-facing layer that Mistral hopes will move it from cool

05:31research shop to everyday fixture inside big company workflows. Social Media Platform delivered

05:38exactly what employees wanted, with driving under pass to laser cut your immersive public speaking

05:43programs down to minutes you don't have to, but bolts on everything a CIO circles in red when they

05:49read an AI RFP. When you wire it up to Google Drive, Gmail, Calendar, Microsoft SharePoint, OneDrive,

05:55or whatever connector they ship next, it does a single pass search across all those silos, then snapshots its

06:02sources so compliance knows exactly where each sentence came from. If the file is a 60-page PDF,

06:07Autosummary skims the cruft, and the model drops links you can audit. The same Medium 3 stack powers a

06:12no-code agent builder, drag a few blocks together, and suddenly the assistant can pull a contract,

06:18update the CRM, and ping legal without anyone writing a cron job. Because everything sits on Medium 3's

06:24cheaper token pricing, finance teams finally get a clean line item instead of three overlapping SKUs.

06:30Security is the non-negotiable. Lachette Enterprise will run a SaaS in Mishra's own cloud, but you can

06:37flip the switch to a single-tenant region, a private VPC, or an on-prem rack, and keep the data inside

06:44your firewall. Access controls are inherited from the source apps, so a board deck locked to the CFO

06:50stays locked. Full audit logs ship out for SOC 2 and ISO paperwork, which matters if you're, say,

06:56a French bank living under GDPR and the incoming EU AI app. That EU angle quietly gives Mistral an edge

07:04with customers who are wary of routing sensitive traffic through US clouds or Chinese open weight

07:10models. Medium 3 and Le Chat Enterprise grabbed the headlines, but Mistral's catalog is getting crowded.

07:16There's Mistral-Large 2, it's GPT-4 class flagship, Fixstral-Large for images and docs,

07:24Codestral for pure code generation, the Liz-Ministral Edge models that squeeze onto phones,

07:31and the Arabic-focused Mistral-Saba. Alright. In March, they even shipped Mistral-OCR, an API that turns

07:39any PDF into plain text so Medium 3 can actually read the stuff. Legal still prints. Some models are

07:46wide open under Apache 2.0, the newest higher-end weights, including Medium 3, stay proprietary so

07:53Mistral can lock down licensed content and offer paid SLAs. That two-track approach is how they square

08:00their original openness slogan with the realities of enterprise contracts. If the roadmap feels

08:06impatient, look at the cap table. Since June 2023, the company has raised about 1 billion euros,

08:12including a 112 million dollar seed that was Europe's largest on record, a 415 million dollar Series A,

08:20led by Andreessen Horowitz, and a 600 million euro mix of equity and debt last summer that parked the

08:25valuation at roughly 6 billion dollars. Microsoft chipped in 15 million euros and hosts the weights

08:32on Azure, while Nvidia, Cisco, Samsung, and IBM all took smaller slices. On the revenue side, paid API usage,

08:40and the 14.99 per month Le Chat Pro plan are growing, but insiders still peg annual sales in the low

08:48eight digits. So scaling fast is existential. Partnerships help. The French army, press agency AFP,

08:56letting Le Chat query every story since 1983. Shipping giant CMA, CGM, and defense startup Helsing all signed up.

09:06Even President Macron pitched Le Chat on TV last week, telling viewers to download the French app

09:12instead of importing ChatGPT. That kind of home field backing doesn't guarantee market share,

09:19but it keeps the spotlight bright, while Mistral chases the numbers needed for the IPO that CEO

09:24Arthur Mensch keeps hinting at. All that context explains why Medium 3 is more than a mid-sized

09:31curiosity. It hits the sweet spot between small enough to run on four GPUs and smart enough to

09:37finish real work, and it does it at roughly one-eighth the cost of Anthropik's Claude Sonnet for the same

09:43token count. For dev teams watching cloud bills spike, a 60% benchmark tie with GPT-4 class models for

09:50pennies on the dollar is a conversation starter. For risk officers, the EU jurisdiction and on-prem option

09:57tick political and regulatory boxes OpenAI can't check yet. Looking ahead, the company is openly

10:04teasing a large release. If Medium is already closing the gap with openweight flagships like

10:10Llama 4 Maverick, a true Mistral Large 3 could yank the high-end leaderboard again. But Mistral's

10:16bigger challenge is commercial, not technical. It has to turn brand buzz and government endorsements

10:22into sustainable post-GAP revenue before acquisition rumors start looking more attractive than the

10:29NASDAQ bell. Mensch told reporters at Davos that the startup is not for sale and a public listing is

10:36the plan, but those words only hold if revenue catches up to that $6 billion price tag. For now,

10:42Medium 3 plus Le Chat Enterprise give them a real shot. If you're tracking inference cost,

10:47on-prem compliance, or just need an LLM that speaks French and Arabic as well as English,

10:52keep an eye on the Google Cloud Marketplace listing that went live yesterday with Azure AI and AWS

10:58Bedrock slots coming next. And if you've already tried the Publicly Chat web app, remember the model

11:04behind the curtain now writes code, summarizes PDFs, and cross-references your SharePoint without

11:09launching a dozen plugins or draining your GPU budget. Whether that's enough to vault Mistral into

11:15the same usage tier as OpenAI is the billionaire question, but at least now they're swinging with

11:21heavyweight gloves. Thanks for watching, catch you in the next one.

🚀🤖 Mistral’s New AI Crushes GPT-4o & Claude 3.7 — And Costs Less Than DeepSeek! 💥💸 | AI Revolution

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