Okay, I'll bite that worm you've left dangling on that hook. Let's go down the list.

Sec. Def:

Biden: Gen. Lloyd Austin. 4-star U.S. Army General with 41 years of active military service. Former Commander of U.S. Central Command (CENTCOM), Vice Chief of Staff of the Army, and Director of the Joint Staff. Oversaw the drawdown of 150,000 troops and massive logistical operations in Iraq.

Trump: Pete Hegseth. White-nationalist alcoholism-scandal-plagued weekend morning co-host for Fox & Friends, former Army National Guard major. Zero executive experience managing large military commands, defense procurement, or enterprise-scale organizations. Opened his tenure by leaking war plans to a journalist by writing about them on WhatsApp instead of secure messaging channels, and is currently losing a war which he promoted launching in Iran, with zero preparation for obvious threats like drones and Hormuz closure, while spending his time obsessing over testosterone levels and beards.

Department of Health and Human Services + Surgeon General:

Biden: Xavier Becerra: 24 years on key Congressional healthcare subcommittees; Attorney General of California overseeing the enforcement of public health and healthcare antitrust laws.
Vivek Murthy: MD/MBA from Yale, Harvard faculty member, practicing physician, and two-time U.S. Surgeon General with deep clinical and administrative credentials.

Trump: Robert F. Kennedy Jr.: Famous antivax-conspiracist brainworm-addled kook who eats roadkill, cuts of whale heads, measures raccoon penises, and swims in sewage. Zero medical degrees, zero public health degrees, zero experience running a hospital system or public health agency.
Nicole Saphier: Radiologist who's a strong advocate of Kennedy's conspiracy theories.

Centers for Medicare & Medicaid Services:

Biden: Chiquita Brooks-LaSure. 30-year veteran of healthcare policy and public administration. Former healthcare analyst at the White House Office of Management and Budget (OMB), key drafter of federal health legislation on the House Ways & Means Committee, and senior official in the HHS Center for Consumer Information and Insurance Oversight.

Trump: Dr. Mehmet Oz. Daytime television talk show host and former cardiothoracic surgeon, widely criticized by the medical community for promoting quack medicine and pseudoscientific wellness supplements on television.

Department of Education

Biden: Dr. Miguel Cardona. Public elementary school teacher, middle school principal, assistant superintendent, and State Commissioner of Education in Connecticut. Holds a Master’s degree in Bilingual Education and a Doctorate in Education.

Trump: Linda McMahon. Professional wrestling (WWE) executive and mega-donor. Most famous for fighting her husband Vince McMahon at WrestleMania X-Seven in 2009 before running for congress (twice unsuccessfully). Before getting into WWE, she earned an undergrad degree in French and worked as a secretary at a law office translating French documents.

Director of National Intelligence:

Biden: Avril Haines. Former Deputy Director of the CIA, former Deputy National Security Advisor, legal counsel to the National Security Council, and Georgetown/UChicago-trained national security legal expert with decades of experience inside the Intelligence Community.

Trump: Tulsi Gabbard. Former congresswoman and Army Reserve officer. Zero professional intelligence community experience, zero senior leadership roles in intelligence analysis or collection. Before her position she was most famously known for harboring sympathies for Russia and Assad.

Federal Bureau of Investigation:

Biden: Christopher A. Wray. Yale law grad; three decades of working as a US prosecutor and attorney general under both Democratic and Republican administrations, including heading the criminal division of George W. Bush's administration.

Trump: Kash Patel. Former congressional staffer, and podcaster. Zero track record in law enforcement. Has spent most of his time in office abusing its perks for himself and his girlfriend.

Department of Justice (AG):

Biden: Merrick Garland. Chief Judge of the U.S. Court of Appeals for the D.C. Circuit (served 24 years on the federal bench). Former Principal Associate Deputy Attorney General who personally led the successful prosecution of the Oklahoma City bombers. Harvard College (valedictorian) and Harvard Law School (magna cum laude).

Trump: Matt Gaetz (first pick). Former congressman who was under active House Ethics investigation for sexual misconduct and illicit drug use; zero prosecutorial experience, zero judicial experience, zero executive law enforcement leadership.

Department of Transportation:

Biden: Pete Buttigieg & Polly Trottenberg. Buttigieg: Rhodes Scholar, Harvard graduate, municipal executive overseeing urban infrastructure redevelopment.
Trottenberg: 30-year veteran of transportation policy, former Commissioner of the New York City Department of Transportation (managing one of the largest municipal transit grids on Earth), and senior federal transit policy director.

Trump: Sean Duffy. Former cast member on MTV's The Real World: Boston, former congressman, and Fox Business commentator. No professional background in civil engineering, transit systems, or logistics.

How many more of these do I need to do?

I'm sorry, but when you look at the current administration, are the people at the top people who scream to you "I reached my position because of my competence and skill"? It is the crowd that's constantly screaming about "DEI" that has been the most obsessed with promoting people based on appearance and personality over any actual competence whatsoever in the fields they're being put in charge of.

And for the record, the guy who led the X mob against this person - Nathan Cofnas - has stated that beyond "whistleblowing", his motivation is that Beyond whistleblowing, he states that after a 'revolution' removes professors like Arday, it will open opportunities for him to become 'head of the department of eugenics and race science at Harvard'. Are these the sort of people whose side you want to be on?

Also, people think they're so clever when they do this, when they generally don't actually work with modern models anyway. It just makes you look manipulative and unprofessional.

It's over an order of magnitude heavier than the largest of those (Helios).

There's a difference between an aircraft being built to lift itself and perhaps a tiny payload and be paperlight vs. an aircraft designed for actual commercial service carrying passengers.

The feet are needed to accelerate the plane to takeoff velocities in order to conserve battery mass.

Also, the big AI companies get a number of advantages, such as large batch sizes and being able to balance on-peak and off-peak workloads better.

Is most of your daily driving "a race"?

This is a midrange model. This is competitive midrange pricing. For my midrange work I've been using GLM-5.2 - Gemini 3.7 flash is a bit cheaper and a bit better on the benchmarks, so yeah, I'll probably switch so long as the prices stay low.

Sometimes you need a high-end model (Claude Fable, GPT 5.6 Sol, Kimi K3, etc). Sometimes a low-end model is fine (GPT 5.6 Luna, DeepSeek 4 Flash 0731, etc). Usually a midrange model is the best balance.

There are to be three variants of the ES-300: an all-electric 200km version, a hybrid 30-seat 400km version, and a hybrid 25-seat 800km version. And the ES-300 airframe very much is not some existing airframe.

EV fires are rarer than ICE fires (and slower spreading as well), so given that the competition is fuel-based....

It is a perfectly cromulent statement. 1MW = power, $5 = a cost of energy. They are providing both power and (indirectly) energy.

They didn't bother to install a co-pilot, a seat for the co-pilot, passengers, seats for the passengers, the hybrid gen set as you say, fuel for the gen set, and who knows if they installed a full production sized battery or just a smaller one

Are you just learning about the concept of a prototype in this comments section?

That's not correct. There are three modes. All-electric, hybrid-30 passenger, and hybrid-25 passenger, with ranges of 200km, 400km, and 800km, respectively. The airframe is to be certified for 20k feet (FL200), with optimal cruise altitudes from 10-15k feet, but this was explicitly described by the company as a "low-altitude test flight".

And to all the people going, "LOL, that's never going to cross the Pacific!" or similar range comments... and? Long haul flights (over 4000km) are only 5% of commercial flights. Very short / regional flights are 27% of total flights. There's very much a market for puddle jumpers, and airlines very much will buy them if they offer competitive advantages.

1) 30B, dense. Optimized to fit Q4 quantized in a 24GB card with a speculative decoding model as well.

2) Because reporters don't know what weights are and assume you don't know either.

3) Way better than Gemma 4 on text tasks, slightly better on multimodal. Numbers below are all: Benchmark: Muse Glimmer score Gemma 4 31B score difference

Artificial Analysis Intelligence Index: Muse Glimmer: 35 30 +5
MCP Atlas (Public): 75.5 54.2 +21.3
DeepSearch QA: 74.6 61.7 +12.9
SWE-Bench Pro: 51.2 36.9 +14.3
SWE-Bench Verified: 76.0 66.6 +9.4
OSWorld-Verified: 65.9 58.5 +7.4
GAIA2: 43.3 36.4 +6.9
WildClawBench: 47.6 37.6 +10.0
TerminalBench 2.1: 51.7 43.4 +8.3
Tau3-Banking: 23.5 15.1 +8.4
MMMU Pro: 74.0 73.0 +1.0
Charxiv Reasoning: 78.8 77.7 +1.1
OmniDocBench v1.5: 75.8 72.5 +3.3
ScreenSpot Pro: 75.4 75.9 -0.4

4) 128k tokens

5) No, sadly.

What you want is a DGX Spark.

It costs $4000.

And yes, there are fundamental advantages to cloud services, such as large-scale batching, little idle downtime, high speed, and hardware optimized to the specific models / serving needs. That said, one can weigh that off against sovereign control over your server...

Define "tolerable".

The model in question - Muse Glimmer - with DFlash/speculative decoding - will probably get you ~60 to 124 tok/s on a 3090 (a quite dated GPU). For a 5090, it's said to clock in at 233,4 tok/s. On CPU you're looking at maybe 3-5 tok/s.

If you call that "tolerable", I guess you're more patient than me? And as mentioned, you're not just wasting time, but also wasting a lot of power too - CPU is a very power-inefficient way to run ML models.

If you insist on CPU, this isn't the right kind of model anyway. You want to take advantage of the fact that you probably have lots of (comparably cheap) RAM, and compensate for the fact that you have (comparably) terrible memory bandwidth, and for that, you want a MoE with a high total parameters but a low active parameters. Not a dense model like this.

Then I was basically aiming at Mac Minis

That's very much a special case which you didn't mention in your post that I responded to, but still the answer is "meh". You couldn't run it at all on a 16GB Mac Mini, and I think you'd struggle to run it at all on a 24GB (because you have to share the ram with the OS, the inference server, etc). For the base Mini you might get 10-12 tok/s, and for the M2 Pro / M4 Pro, maybe 25-35 tok/s. Still pretty far from a GPU, though.

This model is designed for >= 24GB GPUs.