Hilarious sentence: "DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks." (emphasis mine)
It's a bit refreshing to read updates from an AI lab without bullshit doomerism and overwhelming sense of self-importance from shit like OpenAI and Claude.
It passed my threshold for not caring to try new models back with DS4, I use it for literally everything. Announcements of new models in the series always feel curious, because it doesn't really feel like there's much left to fix that would improve on what's already there for any task I know of.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
I have quite the opposite experience: I can do any concrete coding change with any model, but the intelligence limit just doesn't go through more complex debugging examples.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
Also they can work in completely new domains, like Astra and Opus 5.5 starting to be able to use something like Blender. Currently they still often do horrible topology and basic UV mistakes, and the animations are really bad, but who knows where they’ll be in 5 years.
Speed and price. You should try the 4.1 Flash on one of the fast providers. It's pretty crazy how fast this model works, and it's great for iterative software development because you can steer it fast to where you want to go.
Seems that V4.1 Flash is quite cheap to serve. Especially how it implements the cache, meaning the cache pricing can be very low depending on how you implement it in your inference engine.
Depends on your use case. But if you do software development with a harness such as oh-my-pi, your cache rates are probably somewhere above 98%. Coralbricks has free cache reads, meaning it's much cheaper than the Deepseek API rates.
Lithosai is more expensive especially in the ultra tier. It's if you want extremely snappy and fast responses, which is important e.g. for a personal assistant where every second counts.
If you generate a lot of output, you're better off with the Deepseek API rates.
Above GLM 5.3, nice! That is a very capable model. I do wish that we will see some smaller "flash" models again though - running this one locally is tough (very costly).
I use Opus for planning, through API on medium thinking, it doesn't cost anything significant and the rest can be happily done with deepseek or glm flash. Using sol 6.1 for review loops at the end. All running on pi.
A very complex task tends to cost like 10$ max. It's comparable to a subscription with enormous flexibility.
Cant you run it on a pair of DGX spark? Sure it's expensive now, but at the initial retail price that was what, 8k in hardware? Not exactly unachievable
It costs money to run serious tests. We're way past the time when you could get an idea of the new model in a couple of tricky prompts. Now I need to compare a whole resulting project to get a clear view. If someone else proves the benchmarks don't hold up in reality, then it saves us further tests.
Presumably. The current opencode slug for the model is just 'deepseek-flash' suggesting they will just update that one going forward, not keeping versions in parallel.
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
OpenAI's models -- and even Google's Argon -- have particular niches where they shine. For GPT-6/6.1, it's 3D modeling; Astra is hands-down the best at making .step files, Blender files, etc. For Argon, it's natural language writing and everything that hooks up to Google, e.g. search and maps-based itinerary planning.
Anthropic and DeepSeek (+ GLM) are definitely solving coding, though!
Artificial Analysis recently released a dedicated 3D benchmark, where Astra lags behind both Opus and Sonnet 5.5 (and yes, open weight models seem to be quite far behind).
I believe these are the last sets of super-high-end models available to public (open or closed).. these companies probably will now start to withhold top-of-the-line models for themselves, governments, and their super-high-paying partners only.
That hasn't been the way to bet. DeepSeek and the other Chinese firms show no signs of slowing down, so if OAI and Anthropic halt releases and "pace the frontier" they'll just fall behind. (And there's a chance that high-end AI will become fully commoditized, which suits DeepSeek just fine.)
Besides, Fable 5.5 is reportedly releasing within the next few days, probably on Tuesday...
Here's How Distill APT Used McKinsey's Private Access To Top Anthropic Model To Help The Chinese Keep Up With The Us Top IA Labs Despite Access Restrictions
Hilarious sentence: "DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks." (emphasis mine)
Kinda shows their team is more engineers than marketers.
Hoping it's minor relative to what's coming
It's not really contradictory, minor changes can have major effects.
So they meant a "small" update - "conservative", "inexpensive"...
It's about playing to two different audiences.
The CCP requires extensive certification for new major releases, to make sure a model doesn't do anything they don't want it to.
To get around this, Chinese labs only bump versions when they have to and claim it's a minor update.
Then on the other side, they're obviously trying to market to tech crowd...
It's a bit refreshing to read updates from an AI lab without bullshit doomerism and overwhelming sense of self-importance from shit like OpenAI and Claude.
Also, DS is an excellent model.
That is how exponential functions work. Improve every aspect of a system with 1% and you may get easily 50% more performance.
It passed my threshold for not caring to try new models back with DS4, I use it for literally everything. Announcements of new models in the series always feel curious, because it doesn't really feel like there's much left to fix that would improve on what's already there for any task I know of.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
I have quite the opposite experience: I can do any concrete coding change with any model, but the intelligence limit just doesn't go through more complex debugging examples.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
Also they can work in completely new domains, like Astra and Opus 5.5 starting to be able to use something like Blender. Currently they still often do horrible topology and basic UV mistakes, and the animations are really bad, but who knows where they’ll be in 5 years.
Speed and price. You should try the 4.1 Flash on one of the fast providers. It's pretty crazy how fast this model works, and it's great for iterative software development because you can steer it fast to where you want to go.
https://www.lithosai.com/
https://www.coralbricks.ai/
Where does one even get decent ZDR provider? I'm wary of sending sensitive data but not at a scale where I would build my own machine.
How are these high-speed providers close to matching the API rates from deepseek?
Seems that V4.1 Flash is quite cheap to serve. Especially how it implements the cache, meaning the cache pricing can be very low depending on how you implement it in your inference engine.
Depends on your use case. But if you do software development with a harness such as oh-my-pi, your cache rates are probably somewhere above 98%. Coralbricks has free cache reads, meaning it's much cheaper than the Deepseek API rates.
Lithosai is more expensive especially in the ultra tier. It's if you want extremely snappy and fast responses, which is important e.g. for a personal assistant where every second counts.
If you generate a lot of output, you're better off with the Deepseek API rates.
> improve on what's already there for any task I know of
What about "good governance"?
Does it have zero hallucinations? Does it reflect thoroughly on every single idea it uses, verifying its solidity?
definitely could use less thinking time and lower token usage, which is what this bump is focused on
Above GLM 5.3, nice! That is a very capable model. I do wish that we will see some smaller "flash" models again though - running this one locally is tough (very costly).
For comparison, close to Opus 5. Far behind Sol 6.1 and Opus 5.5.
Probably a pretty decent model for 90% of the usecases!
I've been doing a lot of hobby work with GLM 5.3 Flash and I can count the amount of times that I need a stronger model on two hands.
I have access to unlimited tokens at works and Opus is great but also often overkill if you know exactly what you need.
I use Opus for planning, through API on medium thinking, it doesn't cost anything significant and the rest can be happily done with deepseek or glm flash. Using sol 6.1 for review loops at the end. All running on pi.
A very complex task tends to cost like 10$ max. It's comparable to a subscription with enormous flexibility.
It's a steal.
Cant you run it on a pair of DGX spark? Sure it's expensive now, but at the initial retail price that was what, 8k in hardware? Not exactly unachievable
No, this is not a small model. I believe 4x Sparks is possible but 4.1 is pretty big for a flash model.
MiMo 2.6 Flash is the most capable model you can currently run on 2x Sparks without resorting to a quantised version of something.
I meant quantized. You can get an EXL3 quantized version thats almost the same performance.
Looks very impressive especially considering the price and speed. Let's wait for AA to confirm how well their benchmarks hold up.
Why not just try it yourself?
It costs money to run serious tests. We're way past the time when you could get an idea of the new model in a couple of tricky prompts. Now I need to compare a whole resulting project to get a clear view. If someone else proves the benchmarks don't hold up in reality, then it saves us further tests.
It's better than GLM 5.3 and Kimi K3 and way cheaper.
that's honestly insane. it's like the go-to for when you don't want to use opus 5.5/sol 6.1
The go-to is a local model.
Thank you deepseek, we are eating good today.
Those are crazy numbers for a Flash model. Hopefully they can scale what they are doing to 4.1 Pro.
So this is the reason for the crash a few days ago.
What crash?
Deepseek servers went unavailable for 5 hours. They compensated that by rewarding the previous week usage as credit though. Pretty nice.
Ai/tech stock crash
Is it coming to OpenCode et al?
Presumably. The current opencode slug for the model is just 'deepseek-flash' suggesting they will just update that one going forward, not keeping versions in parallel.
and do we know which version runs on opencode at the moment (on the free and on the paid version), is there a way to find out?
Another big win for opensource AI.
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
That's an image China wants the rest of the world to believe. Towards inside it still fits the typical stereotype.
Well, at least mostly everyone outside the US.
Anyone that has observed China since the 90s.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
they must've been using this since 2-3 days when it became free again in OpenCode, it's noticeable smarter, beats GLM
Those benchmarks can't possibly be real, right? Right? <insert padme 4-panel meme here>
At this rate the frontier labs will be Anthropic and DeepSeek, with OpenAI struggling to keep up.
OpenAI's models -- and even Google's Argon -- have particular niches where they shine. For GPT-6/6.1, it's 3D modeling; Astra is hands-down the best at making .step files, Blender files, etc. For Argon, it's natural language writing and everything that hooks up to Google, e.g. search and maps-based itinerary planning.
Anthropic and DeepSeek (+ GLM) are definitely solving coding, though!
They're all quite different tools.
Artificial Analysis recently released a dedicated 3D benchmark, where Astra lags behind both Opus and Sonnet 5.5 (and yes, open weight models seem to be quite far behind).
https://artificialanalysis.ai/articles/aa-3d
I believe these are the last sets of super-high-end models available to public (open or closed).. these companies probably will now start to withhold top-of-the-line models for themselves, governments, and their super-high-paying partners only.
That hasn't been the way to bet. DeepSeek and the other Chinese firms show no signs of slowing down, so if OAI and Anthropic halt releases and "pace the frontier" they'll just fall behind. (And there's a chance that high-end AI will become fully commoditized, which suits DeepSeek just fine.)
Besides, Fable 5.5 is reportedly releasing within the next few days, probably on Tuesday...
News from a near future:
Here's How Distill APT Used McKinsey's Private Access To Top Anthropic Model To Help The Chinese Keep Up With The Us Top IA Labs Despite Access Restrictions
We have the weights, we have the papers, nothing preventing development on this foundation.
idk, sol 6.1 is both cheap and capable. i've been using it exclusively, i don't need to care about usage, and it's really smart.
yes maybe opus 5.5 is stronger and flash is cheaper, but 6.1 strikes a good balance imo.
i have a feeling that Sol is just Astra low, but with lowest possible priority on the compute.
I believe it's Astra quantized. It was briefly named astra-lite.
We're in a crisis
"a minor update" they say before showing off benchmarks that display a substantial improvement.
Censored, no surprise