alt Hacker NewsMiniMax M3.1 Flash
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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.
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...
> 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.
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.
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.
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...
Odd choice to have a mix of opus 5 and 5.5 in different graphics.
I used it as Space Bunny, was very good at documentation, structuring and organizing the things, but was not as concise and direct as DeepSeek 4.1 Flash in coding, we could not focus on code part as a human and AI team from how many approves are needed for each step discussion.
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.
Curious if anyone has put it up against DeepSeek Flash yet, see if the price/performance benchmarks hold up?
Is DHS going to blacklist this one, too? [0]
DHS now plays AI whack a mole, apparently.
[0] https://public-inspection.federalregister.gov/2026-21447.pdf
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.
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
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.
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.
1. Make a new model
2. Add "Flash" to the end
3. ?
4. Profit
Pelicans are pretty solid: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Reasoning traces use truncated English:
> We need provide SVG code. Need creative. Ensure valid standalone. Pelican on bicycle, perhaps detailed vector. Need answer likely fenced svg. Could include title desc. Need be reasonably concise but image quality.
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)
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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
This model seems to be pretty benchmaxed. In actual use, it doesn't survive the comparison to models in the benchmark.
This model was released as a "stealth model" in OpenCode Go for a while as "Space Bunny" (they mention this in the blog). So people have been using without knowing what the model was exactly, but it failed to impress anyone as far as I can tell. This is despite the model being served for free (with some asterisks). GLM 5.3 Flash and DeepSeek V4.1 Flash, even before last week's update, seemed to be much preferred. Stealth releases happen often with OpenCode subscriptions, and GLM 5.3 Flash (stealth name "Ox Alpha") impressed a lot for example.
The perverse incentives around benchmarks are now so bad that benchmark scores are effectively meaningless. Models can score highly and still be crap to use. It doesn't matter whether it's Minimax or Google, or anyone really.