Yet another Hacker News

190 points jtg 2 hours ago 61 comments

swiftcoder 1 hour ago | parent

Curious if anyone has put it up against DeepSeek Flash yet, see if the price/performance benchmarks hold up?

bel8 1 hour ago | parent

Some reddit comments say it's not as good as DS 4.1 Flash. But I didn't test myself and I don't trust benchmarks.

terhechte 1 hour ago | parent

The weights have yet to be released. The previous MiniMax M3 had (I think) ~428B parameters. Since this one is called Flash and they advertise it as inference being 3 times faster, there's the possibility that this will be a ~150B size model which would (quantized) run on DGX Spark or 128GB Macs or the new AMD AI systems.

PcChip 1 hour ago | parent

I think flash usually means MoE, not dense

terhechte 1 hour ago | parent

Not really. “Flash” generally means fast or cost-efficient, not specifically MoE (Mixture of Experts).

- DeepSeek V4 Flash: 284B / 13B active MoE

- DeepSeek V4 Pro: 1.6T / 49B active MoE

- DeepSeek V4.1 Flash: 552B / 8B input, 16B output MoE

jephs 1 hour ago | parent

Every frontier model is MoE these days! Flash or otherwise. Sparsity just gets you more bang for your buck.

penagwin 1 hour ago | parent

The FAQ on their website says Minimax 3.1 flash is 428B total, 23B active

Which is roughly similar to deepseek 4.1 flash.

I find it interesting that we’re calling these “flash” models now, even though they aren’t “small or light” and in many cases aren’t particularly that fast.

I suppose it’s more so that the standard for “regular models” is becoming 1T+

https://agent.minimax.io/tools/m3-1-flash-preview

LaurensBER 1 hour ago | parent

Another day where the Pareto frontier is moved up and to the left!

I haven't tried this model yet but Deepseek and the GLM 5.3 series do feel like "enough" for a lot of tasks, it's pretty amazing to see that we're still getting better and cheaper models all the time.

I only wished they would focus more on wall clock time. For a hobby project I do not mind that a cheaper model takes twice as long but at work it's hard to justify using a "cheaper" model if the time per task is so much higher than the frontier models.

The amount of time that it took to complete a benchmark is almost never shown in these kind of releases.

theanonymousone 1 hour ago | parent

> Another day where the Pareto frontier is moved up and to the left!

It actually hasn't, it seems: https://news.ycombinator.com/item?id=50151775

antisthenes 1 hour ago | parent

You do realize that there exist multiple Pareto frontiers, at least for every arbitrary combination of parameters for a given benchmark?

Obviously your marketing team is going to use the Pareto frontier where your model has improved the most and compares favorably against competitors.

rskeens 1 hour ago | parent

Would place DS 4.1 1017 roughly equivalent to GLM 5.3 which means it's targeted to price rather than direct capability. Probably why they listed DS adjacent in the comparison table when according to their results more expensive models are beaten by it.

hebelehubele 6 minutes ago | parent

Is DS 4.1 as capable in reverse engineering and cyber security?

theanonymousone 1 hour ago | parent

Dupe, dupe, dupe, dupe, and dupe:

https://news.ycombinator.com/item?id=50151561

https://news.ycombinator.com/item?id=50151576

https://news.ycombinator.com/item?id=50153196

https://news.ycombinator.com/item?id=50153612

https://news.ycombinator.com/item?id=50153725

theanonymousone 1 hour ago | parent

@dang maybe?

bigwheels 1 hour ago | parent

Friendly reminder: Submissions without discussion aren't considered dupes on HN.

theanonymousone 1 hour ago | parent

Oh, really? I didn't know this. Sorry.

Then maybe they can be merged once one gains a comment?

himata4113 1 hour ago | parent

Sometimes it will automatically redirect to an already submitted one, but the system is not perfect and you might end up with duplicates like this.

minimaxir 56 minutes ago | parent

There is literally no reason to merge them if they have zero discussion. Submissions to HN are not a finite resource.

thenthenthen 1 hour ago | parent

Amazing haha. Why is it so quiet around hy3/hy4? Or Tripo? Or agitbot or z.ai? All incredibly capable

minimaxir 58 minutes ago | parent

Apparently the domain is shadowbanned (https://news.ycombinator.com/from?site=minimax.io) which is why people kept submitting it (and normally they cannot be vouched), and presumably a moderator gave this one their blessing.

The solution is for @dang to unshadowban it because Minimax is now a newsworthy company.

yorwba 53 minutes ago | parent

They were a newsworthy company when their domain got shadowbanned, too... The spam detector is blind to such things.

loufe 1 hour ago | parent

Odd choice to have a mix of opus 5 and 5.5 in different graphics.

tcdent 1 hour ago | parent

The recent DeepSeek release used Opus 5 as a reference point as well. I don't understand it. It's not like they're referencing superseded releases of other open models.

tadkar 1 hour ago | parent

Most probably the last version they had access to for benchmarking, or otherwise.

jrflo 30 minutes ago | parent

I'm assuming they are just going off published benchmarks and not re-benchmarking other people's models

minraws 1 hour ago | parent

I think it clearly points to where they expect themselves to be, Opus 5.5 and Astra or Sol 6.1 are models that shouldn't exist at those prices without the price competition.

And no new releases from Chinese labs likely means their models that they could compare against those models are still baking largely because they lack compute so severely they need to train models for far longer, or figure out training on Chinese hardware.

Either way it's clear open models a lagging by ~1-2 months compare to frontier, depending on what frontier means to a person. Honestly most new models are just not that much better than at edge cases, they still fail a lot for the kind of stuff I do, but those edge cases matter a lot for un-interrupted long horizon work.

I personally am starting to see a wall here in llm development but that might just be me, given that people are being forced to scale models up considerably for frontier performance.

It's scary thinking that modern models will likely be at best 2-3% better in benchmarks or only useful in 1-2 unique edge cases compared to base models for 100x cost increase in compute required, it's getting absurd.

I can't imagine how Fable models can retain any value once you have to go 100x larger, while 27-32B models start to catch up to the current frontier for coding or other narrow/focused tasks in a year or so.

bitexploder 9 minutes ago | parent

Models like Qwen 27B 3.8 and Flash Next 3.8 show there is a lot of room to pack more into less parameters.

jrflo 26 minutes ago | parent

I went to check and Opus 5.5 wasn't benchmarked on DeepSWE1.1, I can't keep track of which are in vogue at the moment but maybe it's thought to be saturated at this point, as they only have older GPT models as well

bitexploder 13 minutes ago | parent

Artificial analysis has benched it on deepswe

johnnyApplePRNG 1 hour ago | parent

Not as strong as DeepSeek V4.1 Flash 1017 on deepswe so it's already dead to me.

Unless they come in at half the price (which I think will be impossible) on inference ... they have wasted their training compute imho.

trilogic 58 minutes ago | parent

Minimax has been a strong player in our tests, if they managed to solve the inference speed issue(be scared, be very scared). A decent speed is at least 13 tps in consumer hardware. Let see if it passes Hugston bench this time, we really hope so.

latentsea 55 minutes ago | parent

13 TPS is painfully slow?

20 t/s is about the speed you can read at, so slower than that and it always feels like it's buffering. 35 t/s is where it starts feeling decent and 50 t/s feels nice.

trilogic 45 minutes ago | parent

I know, it is never enough, more, more, give me more. But the fact is that no one has broken though yet to offer a frontier like open weight over 13 tps in consumer hardware. It would be usable at 13tps for me, especially considering the benefits and advantages of privacy, infinite tokens, availability and no refusals/restrictions. To this day Minimax and GLM are very strong coders but have the same issue, inference speed. We need a real break through, one that thinks out of the box (Tesla turbines style perhaps).

mickeyp 35 minutes ago | parent

If all you're going to do is chat with an AI, you don't need a 400B parameter MoE model.

13 TPS is unusable for agentic coding, because if decode is that slow, then prefill is absolutely abysmal, and agentic work live and die by prefill speeds.

redanddead 26 minutes ago | parent

Why does agentic work live and die by prefill speeds?

bitexploder 14 minutes ago | parent

It doesn’t. Decode is by far the most dominant and expensive part of agentic tasks and once prefill hits a certain achievable speed decode dominates the time in ant agentic flows with reasoning. There is a reason input is so much cheaper :)

genxy 18 minutes ago | parent

> If all you're going to do is chat with an AI, you don't need a 400B parameter MoE model.

Why wouldn't I want the smartest possible model I can get? I only "chat" about smart person stuff.

sosodev 18 minutes ago | parent

I’ve been agentic coding at home with like 15 TPS on average. I don’t mind it at all. I can give my agent a big task or a list of little ones and just… do something else. Why do I need to watch it work?

wmedrano 5 minutes ago | parent

It feels even slower when you consider thinking traces and tool calls which are skimmable at best.

walrus01 58 minutes ago | parent

The deepswe and terminalbench4.0 scores don't seem to jive with what many opencode users' experience has been of this model while it was being tested as "space bunny". I saw a lot of anecdotes of people trying it and going back to qwen 3.8-flash-next or deepseek v4 flash because "space bunny" made some rather egregious errors.

penagwin 41 minutes ago | parent

> [Space Bunny] was an early version of MiniMax M3.1 Flash.

They mention that space bunny was an earlier checkpoints, so it may have improved (or may it could be benchmaxxed)

I find it interesting that so many models seem to be at almost exactly 74% specifically which makes me suspicious of the benchmark. I want to say 5.6-sol, Astra, deepseek flash 4.1, opus 5 (and 5.5?), Gemini 3.8-flash and a few others all ended up there?

syntaxing 52 minutes ago | parent

The cost vs performance is insane for all these new models. I’ve been using Deepseek Flash 1017 and it does whole projects and asks for $0.10 on US provider with ZDR on Openrouter. I convinced a few friends to drop their Claude $20 subscription because DS Flash 1017 brings so much better value. They can still use Opus 5.5 for planning though each call will cost north of $2. Excited to try this model out too once there are US providers.

redox99 44 minutes ago | parent

Opus 5.5 is according to AA cost per task, 23x more expensive than Deepseek with max effort (which is dumb, you shouldn't use) and 13x more expensive on xhigh.

Claude sub has a 60x subsidy, so a $20 sub gives you $1200 in API.

Based on this math, Claude sub is a much better deal than Deepseek. And it's a stronger model of course.

genxy 42 minutes ago | parent

He is trying to be faster than his friends, not the bear.

MisterMunchkin 24 minutes ago | parent

Lmao this is real anslopic math.

switchbak 13 minutes ago | parent

I pay API rates via OpenRouter / Fireworks, and I find it challenging to hit the $20 mark.

If I was to do anywhere near that kind of work on Anthropic, I'd find myself running out of tokens, waiting days to continue working, and leaning on their el-crap models to try to avoid running out again. This happens all the time.

This way I get to leverage DS for nearly all my work, benefit from its far superior latencies, and I still get to lean on OpenAPI / Anthropic or whatever SOTA models I want when I need them.

The only time that really falls down is if I'm doing huge amounts of real novel work, which hasn't been the case for a while.

MrZander 3 minutes ago | parent

[delayed]

varispeed 51 minutes ago | parent

The comparisons with models like GPT-5.6 or Opus are pointless because they vary substantially. They are often nerfed shortly after release and then performance is not consistent. One day model will be doing relatively fine, another it will be dumb as markov generator. In that regard self hosted models are better, because you know what is running your requests.

redanddead 22 minutes ago | parent

This is thought to be conspiracy thinking but I don’t think it is

minimaxir 45 minutes ago | parent

> For agentic tasks, the model’s overall usage cost is 70% lower than its predecessor.

For this release, the cost is $0.15 input MToK/$0.60 output MTok/$0.015 cache read MTok, In this case the predecessor is MiniMax M3 (not Flash), which was $0.30 input MToK/$1.20 output MTok/$0.06 cache read MTok. So a 50% cut to input costs and a 50% proportional cut to cache read costs (20% of input -> 10% of input) makes the ~70% cost reduction plausible.

A 70% cost reduction is very funny in light of reports saying LLMs are becoming too expensive. That is likely due to the need to compete with DeepSeek V4.1 ($0.15 input MToK/$0.60 output MTok/$0.003 cache read MTok), which this new model still does not beat because DeepSeek's cache costs are still confusingly low, but it's pretty close.

wolttam 27 minutes ago | parent

If anything I am confused by how high cache costs still are across many models

The really expensive part of inference - the compute and memory traffic required to perform prompt processing and decode - is paid for roughly once per token in a multi-turn session when prompt caching is working properly.

The difference to the provider's costs between:

- Submitting 100 back-to-back requests, each adding 1k tokens to the context

- Submitting 1 100k token context request

Is negligible. Yet the consumer is going to pay a lot more in the former case for all those repeatedly submitted input tokens that you get charged the cached rate for (but which required no additional compute on the provider side).

DeepSeek V4.1 has an insanely optimized KV-cache that takes around 900MB per million tokens, making it feasible to move to disk between requests. Makes sense they're cheap

dang 38 minutes ago | parent

Recent and related:

Ask HN: Any guesses on which model/provider is Space Bunny Alpha on OpenRouter? - https://news.ycombinator.com/item?id=49898971 - Sept 2026 (1 comment)

minimaxir 29 minutes ago | parent

this comment was dead and I had to vouch for it

lisplist 14 minutes ago | parent

MiniMax models have been pretty disappointing. M2.5 was good, M2.7 was meh and came with a terrible license, 3 meh. Maybe this will be better, but I have my doubts. When I say good vs meh vs bad, this is all relative of course. If M3.1 came out a few months ago it would be groundbreaking. Things just move too quick.

H3, on the other hand, is phenomenal

mawadev 12 minutes ago | parent

I go off of marketing obviously, but how is every new announcement of any vendor always on top of all others and then cheaper, while next day the next best and even cheaper model pops up? Is there anyone who independently verifies this? Its kind of pointless to comment on this announcement, much like how its pointless to comment on all the other announcements...

julianlam 7 minutes ago | parent

You have to read between the lines (or wait for someone on HN to do it for you).

It's never "cheaper and faster and more intelligent", it's pick 2. Sometimes (as was the case this month), it was "cheaper per token, but reasons five times as much", so your costs go up.

cyanydeez 6 minutes ago | parent

the nice thing about local models is you can limit reasoning and keep things even all the time.

60secs 8 minutes ago | parent

Is there a single use case where you would not be better served using MiMo 2.6 Pro?

https://artificialanalysis.ai/models/comparisons/mimo-v2-6-p...