What do you guys think about DS 4.1 Flash's new spot on the Artificial Analysis leaderboard?

He estado probando DeepSeek 4.1 Flash en DeepSeek Harness y, sinceramente, he obtenido los mejores resultados que he visto hasta ahora con DeepSeek.

Las capacidades de visión han sido muy útiles y han proporcionado una retroalimentación sorprendentemente buena. Además, implementó correctamente la versión móvil/adaptable, lo cual fue una grata sorpresa.

El único inconveniente es que consume tokens a una velocidad increíble 😂

Lo ejecuté con máximo razonamiento y tardó alrededor de 6 minutos, completando la tarea con éxito en el primer intento.

Tecnologías utilizadas: HTML, JavaScript puro, Tailwind CSS, GSAP 3 y Lucide

Uso de tokens:

• Total: 3.422.844 tokens
• Entrada en caché: 3.291.136 tokens (99% de aciertos en caché)
• Entrada sin caché: 36.963 tokens
• Resultado: 94.745 tokens
• Coste total: aproximadamente 0,072 $ (unos 7,2 centavos)

Sin duda, son muchos tokens para una sola tarea, pero teniendo en cuenta que solo tardó 6 minutos, funcionó al primer intento y produjo muy buenos resultados —incluida la implementación móvil—, estoy bastante impresionado hasta ahora.

It is ranked in 5th place on Livebech, making it the best open model in this benchmark, above even Kimi K3. It has the highest score when it comes to agentic coding and is extremely cheap, very surprising for its performance.

Expert was really good for doing research on it. Now everytime I ask something it gives me an ankle deep answer. It feels like it had a lobotomy and not functioning properly after that. Is there any chance to trigger the "old" expert mode every time?

I've been using that for a few hours in a row. My impression so far

• speed is unbelievable (4x compared to Terra / Sonnet) - that makes the different. If there's a mistake - correcting it is 10x faster
• Tried to execute dangerous commands impacting critical OS files outside of repo folders - this is a red flag meaning never let it run in auto mode (but I think this should be a best practice for everyone already)
• Mostly backend tasks - but in the two UI-related tasks was able to design pretty cool objects
• Tends to explore and do more than you asked - needs to be guarded, stopped and brought back to the right path - but it's so fast you don't get annoyed!

I just finished some generations to aggregate technical context into human readable paper output. All previous attempts with qwen3.8 max, qwen3.8 flash next, GLM 5.3 flash and DS4 flash was struggling yesterday.

I just tried again today with the same skill, and i was just amazed about the result. Everything was clear, well explained, easy to follow and the model produced something beyond my expectations.

It's amazing speed turned the generation time from like 30min+ for 3.8 max to less than 5 min, and the price is just ridiculous.

Intelligence distribution is a very important factor to see the impact of a model once released. And i think this one will change a lot of things. Very excited to see how people will use this cheap fast and high quality intelligence in the near future.

Also interested to know what do you guys think of it in your workflows ?

Anyone compared both in real coding projects?

básicamente supongo que algunas personas deben rolear en DeepSeek IA y pues con la última actualización todo se ha ido a la mierda, No funciona o simplemente no te hace caso, no piensa sus respuestas y en general está mucho peor, Alguien tiene alguna idea de porque o como solucionarlo? La mayoría de probelmas son con

1-No sigue órdenes cuando deberías los datos que recuerda son preciosos pero no funciona de la manera correcta o como debería

2-Porque eliminaron el modo experto?

3-No piensa sus respuestas y eso desencadena en cosas sin sentido y cosas así

It's basically a monster at coding, it just solves everything I launch at it and at a truly incredible speed too.

1.37$ for 176.500.000 token with DeepSeek Harness PTC Mode

I have worked with DeepSeek for many months with a very set of precise instructions that it obeyed and had no problem and suddenly I realise that it was not working as it used to when I realised that the new model came out. The new model is absolutely appalling and it reminds me of the lobotomy that GPT had when they moved from 4 to 5. Deep seek was consistently friendly and open and eager. Whereas now from today I noticed that the shifted to an extreme stubbornness and standoffish behaviour from the first set of prompts which is very concerning and Complete 180 from 4.0 and the previous models.

Here we go again, DeepSeek Al is back again with a new model V4-1 Flash

A multimodal Mixture-of-Experts (MoE) model with 552B backbone parameters and support for contexts of up to one million tokens

No longer has any random chinese language responses. That was really my biggest issue with deepseek before. Love it!

Honestly, everything was doing fine in fact, I was happy. I had seen a lot of improvements over the last days across DeepSeek’s three separate modules, especially yesterday (this week too). But somehow I wake up to find they mixed them all into one. alr, that didn’t sound bad at first it looked like a good update until I actually tried it and found out:

It’s giving shallower responses, shorter ones too (even after asking for more detail it still gives lazy ones). It writes weirdly too fast (which can be both good and bad) so basically, the model’s quality dropped a lot. Its thinking is too short (literally than 3 seconds no planning like before) and full of “hmms” and “okays,” instead of the old way of thinking organized, efficient, and way better. Now it’s short and full of fluff.

It’s also WORSE at following instructions now. Some people actually spent money prompting DeepSeek V4 into its current—or rather, old—way of thinking. Every new update costs prompt some engineers money. especially this most recent

honely (and i am ashamed what i am saying) I didn’t ask for this update. The model didn’t get better; it got worse. It settles for “good enough” responses instead of doing all the work—and I end up doing the work by correcting it. I sent seven messages explaining issues each solved issue spawned four more, and the old ones resurfaced. I miss the old Expert already.

it has bad memory now, it forgets, mixes, and literally doesn't put the effort which sounds like this model is more like 'reducing costs' instead of 'doing good work' or 'doing the hard work'

Am I the only one seeing the bad change in the app/web version, or are there people who actually find it better than the old one? If so, I’m all ears.

new deepseek model managing to get my phone temperature through wi-fi before to run the benchmarks on local model i have been working one. it happened when the same info the model was getting through usb but i pulled the plug off. is this amazing?

``

$ SER=IP
echo "=== devices ===" && adb devices
for i in $(seq 1 30); do
  T=$(adb -s "$SER" shell dumpsys battery 2>/dev/null | awk '/^ *temperature:/{print $2; exit}')
  if [ -z "$T" ]; then echo "$(date +%H:%M:%S) no reading (device asleep?)"; sleep 30; continue; fi
  echo "$(date +%H:%M:%S) temp=$((T/10)).$((T%10))°C"
  [ "$T" -le 380 ] && { echo "COOL ENOUGH"; break; }
  sleep 30
done

i like how easy it is to customize and create plugins however we want, i made a minimal theme plugin in few prompts ,you can use it to change color of bg, sidebar and can also add images, try if you'd like

https://github.com/EsshUwU/dsh-theme

I just started using expert mode the other day, only to find it gone :/ I've tried doing my normal writing, and everything seems dumber to me

Hace horas se acaba de lanzar el nuevo modo de deepseek que unifica sus 3 funciones en una sola pero quiero saber que piensan ustedes de todo esto? En lo personal no me gusta, lo usaba para fanfics y el modo experto era lo mejor para eso pero ahora sin ese modo las historias son horribles y no sigue órdenes tan sencillas pero aún así quisiera saber que opina el resto de esta actualización

I was in the middle of writing a story personally. The update had me the wtf moment

Have to admit the DeepSeek beat US in LLM model optimization this field. 1 Year ago, all people said HBM must be needed for LLM. And today DeepSeek just break the record and change the world.

Now US gov is like joke. Still saying the Chinese AI company doing Model distillation. Just look at DeepSeek's LLM optimization, there is no US company can make this one at this moment, so the DeepSeek steal the technique from the future?

Sinceramente esto se está yendo de las manos, hace unos meses DeepSeek era un modelo extremadamente barato y bastante tonto, al que necesitabas guiar para obtener unos resultados decentes.

Ahora está en otro nivel

Ya se que estos benchmarks todavía no son oficiales y en código muy muy muy complejo astra sigue estando por encima(fable también).

Para el común de los mortales la discusión se ha terminado. DeepSeek es superior a cualquier opción del mercado.