MAI-Code-1-Flash

Makes sense as part of a larger coding workflow, especially if it’s fast. Using a trillion parameter model to figure out how to call a targeted edit tool or generate a commit message is a waste. Also narrow tasks like “make the background darker” or “rename this function and update callers”

What application/UI are you using deep seek flash high on? Still copilot or something else

I use larger models to organize work into a topologically sorted task graph and pin smaller models to the tasks depending on the complexity with a larger model evaluating the work and patching where necessary. This uses haiku quite often for routine work. I’m able to do multi hour highly complex work with superior results and a much lower bill as a result by doing this, with a parent orchestrator able to do a massive labor within a single context window by effectively organizing work and reviewing quality and integrating where needed. I don’t use haiku directly, but it’s often 30-40% of any major efforts token use. This further improves time to completion as well as cost - but I find haiku is better at following literal instructions and plans without “second guessing,” while opus class models second guess in their thinking constantly.

As such, haiku isn’t a waste of my time, it saves enormous amounts of time for me. But I spent a large amount of time building the orchestration system up front and iterating on it to get here. Interestingly i found my experience as a director and later a distinguished engineer gave me the tools to build it and get it working well and reliably end to end - the dynamics of multi agent workflows of varying capability is not a lot different than the dynamics of a 1000 engineer organization.

I've been doing benchmarking of various models for finding hard security bugs, and my faith in Haiku (and Sonnet, even) has dropped precipitously in the process. Self-hosted Qwen 3.6 27B consistently outperforms both for finding security bugs, which was a shocking result. I expected Qwen to be around Haiku level, maybe a little worse, and I definitely expected it to be worse than Sonnet.

And, DeepSeek and MiMo perform much better than Haiku and Sonnet, near Opus/GPT 5.5 levels, at a fraction of the cost.

There's seemingly no reason to ever use Haiku or Sonnet, if you're not getting it for free or as part of a subscription (that you don't usually saturate).

Almost exactly the same story here. I've also had little to no refusals from DeepSeek, with it's Chinese values meaning substantially less friction when it comes to things like reverse engineering, finding copyrighted files, working with dubiously-sourced source code, et cetera. I don't think I'd go back to Copilot even if they dropped prices by 90%.

Yeah, seems like this is in the range of Qwen 3.6, Gemma 4, Nemotron 3 Super, and the like. There are lot of models, including much smaller cheaper ones (like Qwen 3.6 35B-A3B), that are similarly competitive with Haiku. I can run these on my laptop, I don't need to rent them from Microsoft.

I suppose if you're reeling at the new Copilot bill but want to stay in their ecosystem, this gives you something to use, but for most folks, there's a plethora of better options.

The small stuff has their place. I have this safari extension and needed a way to quickly title people's chat histories. Haiku is the fast cheap thing to come up with decent titles of blocks of text. I feel like there's a bunch of those little things lying around you need a model for. I'm even finding Apple's Foundation Model is super useful for stuff like that. Even summarizing an article. It's like equally awful at doing it, but gets enough done to still be useful as a way to be like "oh yeah, this article is actually worth reading"

Haiku does quite well if given a detailed plan. That means much more detail than you otherwise would, but you can still save over e.g. having Opus or Sonnet do everything by having them expand their initial plans into more specific levels of detail and feed it to Haiku (or similar level models).

I personally wouldn't use models that class directly, though - I'd use them in a harness as a "backend" for more capable models. And Haiku itself, as opposed to other smaller models, is still expensive.

The $20/month ChatGPT plan that comes with codex is good value. Even just have premium ChatGPT is nice. I get rate limited regularly but it still lets me do most things.

Won’t (presumably) all the market actors converge on similar pricing? If OpenAI stopped operating on subsidies and charge the true costs and their most token hungry customers are the ones that switch to Anthropic and others, then their pricing model switch will also be around the corner.

Unless of course we’re thinking Copilot will be more expensive than others longer term. But is that a reasonable assumption?

I've been having really good results with DeepSeek-v4-flash, qwen-3.6-moe, and the older gimini-3-flash-preview. (recent geminis suck hard)

Small models are more than enough for the majority of tasks these days. Plan and review with the bigger ones, let the little ones explore and implement.

OpenCode Go is $10/month for the open weight models with nice quotas: https://opencode.ai/go

> "GitHub Copilot had competitive pricing until yesterday when they changed from per-request to one of the most expensive per-token quotas. Seriously, take a look at their burning subreddit for some laughs"

AI is expensive and it has been heavily subsidized. I you think $20/mo for Codex/Claude flat vs a more usage based model you're in for a shock. Especially once these companies go public and have to meet investor expectations.

I wonder when THEY make it illegal to vote with your wallet.

The take away is that this model is a smaller model that competes with Haiku, I would hope they come out with a "Sonnet" competing model, then Opus. I have been wondering why Microsoft is kind of "sleeping" on offering models they themselves have made on Copilot, maybe it was part of their deal with OpenAI? Not sure.

> 137B-A5B

Yeah, not a 5B param model as the earlier title implied!

[dead]

Definitely vibed microslop, the giveaway is the broken header and scrolling on mobile.

Brand guidelines and web design pretty much don't exist any more as far as I can tell. Gotta get it out yesteday, and the only way to do that is vibe coding, styling be damned.

Thank you! This website is dreadful for accessibility and usability.

That's neither Microsoft nor Anthropic design. It's from their acquisition of Inflection AI. Even Copilot mobile app design is basically what was Inflection's design

maybe it was coded by Claude

i think it is AI generated.

This is needlessly embarrassing, seems like a small thing, but it makes them look... desperate?

A little to minimalist - only a few hundred words on entire page!

I am using Opus 4.x at work, and these "smaller" (20-80bn, 3-4bn active) models at home. Unfortunately there is no comparison, yet (IMHO anyway).

With Opus I can work, trust its designs, architecture suggestions, and code changes, even in a complex code base.

The smaller models seem to "try". They work for smaller tasks, but for more complex task it's often more work than doing it myself.

I wish it were different, and maybe in a year or two it will be.

Because the Haiku model is quite cheap but doesn't screw up too often I used it for interactive coding for my existing projects on the older copilot plans.

For simple features I don't have a full plan worked out. I write a bit of code then tell the model in a short line prompt what it should do. Sometimes I put temporary comments in the code to give it guidance. Generally if the code change is within a file or package, Haiku is good enough follow what you ask and not mess up too much. I also have skills created over time to give it guidance. There were some months when I used GitHub copilot where I had excess credits available at the end of the month I frantically try to use up.

Even the AI code completions can be pretty good on their own. Sometimes I write some temporary comments describing what the code should do and just press Tab-Tab-Tab and the entire function is done.

I think there is a tendency for people to go for the advanced models thinking they we screw up less but if you really understand the code its easier to interactively do it with a lesser model.

>Is the play to plan/design/architect with a heavier model than delegate structured tasks to these smaller ones?

always has been

claude code has opusplan — uses opus while in plan mode, switches to sonnet for execution.

https://code.claude.com/docs/en/model-config#opusplan-model-...

edit: you can make it work with sonnet for planning, and haiku for execution, or any other combination you fancy to work with.

https://code.claude.com/docs/en/model-config#control-the-mod...

Not sure if considered it's considered small in any way, but DeepSeek V4 Flash is really decent.

Yes. Divide execution of a change into separate responsibilities. Designate the main chat as the "orchestrator", Opus. You designate a goal, then tell it to grind until it gets there using the following sub-agents in sequence:

1. Step execution (Sonnet): Work for 30 minutes / 100k tokens at the direction of the Orchestrator

2. Review (Opus): Scrutinize the previous step's work for errors, fidelity to the instructions, fix those and record opportunities to improve the agent configuration + tools to reduce errors and token usage (record those to a file).

3. Self-improvement (Opus): Implement the highest impact self-improvement items that don't require user intervention.

Repeat: Until orchestrator session token budget exhausted (set it to 1M or whatever).

The underlying rationale is to keep each step manageable to maximize adherence to instructions and minimize cost (even cached tokens cost something). Prompt tokens are much cheaper than generated, so to the extent Opus mostly reviews rather than drives that saves a lot too. Self-improvement steps are very expensive but the improvements compound, if you're going to run a job for days or weeks it's way more expensive not to do them.

Edit: I do this in Claude Code with the Anthropic models as well as Qwen family models for offline use.

Claude code itself spins a lot of its subagents with Haiku. The model has low hallucination rate, so it is great for exploration tasks. I guess this is what the best purpose of this model here will be as well. Which is a lot of tokens - many tasks spin multiple exploration agents before the planning or fixing, that is then just a few tool calls.

I was wondering the same. I guess it makes sense to use a heavy weight model to make the entire design and split the work so that smaller models (possibly local one?) would then do the coding... But how would I even do that? I'm using Claude Code. Would I need support for this within the harness ?

I use Gemini 3 Flash, I've seen the Claude Code setups, bullish on Anthropic people are driving up tokens but I am able to produce outcomes with a fraction of the money.

From my experience, smaller models like Haïku 4.5 have indeed shown very convincing results on specific, scoped tasks (themselves generated by a more capable model such as Opus 4.6). We use this kind of workflows in production to optimize speed, efficiency, and costs.

i used to use opus for everything, thats not an option once you move to a multi agent system unless you're working on like high end research. I could easily spend 3k a day if i was using opus as just a normal dev.

As we build a better and better harness and better feedback/verifiers we're switching more to 3.5 flash. I think chinese models would work too, but we cant use those atm.

Generally theres a coordinator running opus and an ever growing set of skills and subagents that take actions using weaker models and output feedback to the coordinator opus.

I'm pretty convinced at this point we're past the level of intelligence needed for most tasks most devs do and that will trend down as we better build harnesses for our own codebases.

Implicitly, yes. A lot of harnesses will invoke small models to do small changes, saving time and tokens.

plan using opus execute using local

I keep trying to, because I really want to make qwen 3.6 35b work for end implementation of a fleshed out spec (mostly for local data privacy reasons).

...but I spend so much more time correcting it, or building pipelines to try, retry, and converge, that it's rarely worthwhile for me in either time or $ spent vs Opus.

I use it for smaller changes that I need to make, mainly on UI fixes or some easy logic fixes.

In DeepSWE anything from Antropic is a whole class lower than what's achievable with gpt-5.5

So by using Opus you are using "smaller" model. Well, not really smaller, just worse. The actual smaller models can at least be faster.

I actually find planning/design easier with a smaller model and implementation with a larger one. I'm mostly manually working with the model on planning and design and decisions are mine and smaller models are faster. And when there's a clear design/wayforward, the bigger models are usually better at understanding the overall context and applying the specific patch they were assigned to. I call it the 1-2 punch system where you do the first light punch then the harder punch when its actually important to hit properly. I know it goes against the standard of throwing the biggest model at design but I personally experience the bigger models try to do TOO MUCH and take a lot of time which is something that's not good in the design/arch/boilterplate phase.

from what I understand, it's because unlike the other models, MAI models haven't yet fine-tuned against the synthetic datasets specifically designed to boost the benchmark scores.

It’s about bang for buck. That high a score for 5B params is pretty good, nigh unbelievable a short while ago.

It is my belief that smaller models will get better and better, and even cloud SOTA models will shrink.

Yet another reason the current buildout will feel like the railroads.

Thanks! I've changed the top link to the blog post and put the other links in the toptext.

Maybe the next Windows update will change This PC back to MAI Computer. ;)

That's not accurate. Take a look at the paper to see what it is trained on! And specifically decontamination is called out in A.4

https://microsoft.ai/wp-content/uploads/2026/06/main_2026060...

What is your evidence for this claim?

some kind of scroll hijack going on for sure, feels terrible on firefox+macos

Have you tried system design with LLMs? I find them pretty good at suggesting 5 architectures for a problem and then iterating on the solutions.

Even if I had no idea, going with the default suggestion would not be a terrible mistake, assuming you did describe your requirements relatively well.

:(

I was hoping Microsoft would make it open weights, as they have done for years with the Phi models.

The era of big tech releasing models into the wild might be over, which IMO is counter-productive, as we are shifting from "the model is the product" to "the harness is the product"

Fix:

  (() => {
  const KILL = ['wheel', 'mousewheel', 'DOMMouseScroll', 'touchmove'];
  const block = e => e.stopImmediatePropagation();
  for (const t of KILL) {
    window.addEventListener(t, block, { capture: true, passive: true });
    document.addEventListener(t, block, { capture: true, passive: true });
  }
  document.documentElement.classList.remove('lenis','lenis-smooth','lenis-scrolling','lenis-stopped');
  console.log('Scroll hijack disabled — native scrolling restored.');
  })();

Yeah this website is horrendous to use. What were they thinking?

[dead]

Meta recently launched Muse Spark [1] and they themselves compare against Claude Opus 4.6 Max.

Here Microsoft is comparing against Claude Haiku, the smallest and least capable model from Anthropic.

[1] https://ai.meta.com/blog/introducing-muse-spark-msl/

Wait… I think he has moltbook IP as well that he can scale up.

Seriously tho, wtf is going on over at Meta? Anyone working there currently want to describe the vibe of the org when it comes to being a frontier company?

From https://news.ycombinator.com/newsguidelines.html

Please don't complain about tangential annoyances—e.g. article or website formats, name collisions, or back-button breakage. They're too common to be interesting.

even worse on mobile

Microsoft has been releasing LLMs for years.

> I always prioritize speed over raw intelligence for flash models.

This model might have a perfect speed:

    for i in range(100):
      print(random.choices(words))

It claims that, then promptly proceeds to showcase a bunch of benchmarks.

You aren't wrong, the field is moving to a world where we do less in the code editor, so autocomplete is not needed any more. I've only manually edited code a few times in the last month. Haven't used autocomplete in 6+ months since I left Copilot to build my own agent harness (I'm now mainly using OpenCode)

Claude opus 4.6 scores 51.9% on the same benchmark. Microsoft's result is quite good.

51% does not mean it randomly gets things wrong half the time.

These things can be useful if you can accurately predict which tasks they will reliably do, and which they will usually fail on. Then you can get much more reliable work from them.

Please share the script

Please share

They're comparing to Haiku, not Opus. Haiku is currently at 4.5.

Even if it were Opus, comparing to a version number makes for an interesting snapshot of time comparison: if you knew how a model performed at whatever time in was in vogue, you can say "well, it looks like Model X is about 6 months/1 year/etc. behind the frontier SOTA" - which is exactly the discussion that happens in the open-weight/local LLM space. (interesting, MAI-Code-1-Flash does not appear to be such an open-weight model, following the western trend of locking models up)

Latest Haiku (smallest Anthropic Model) is version 4.5, they haven't released a new version, hence the comparison to that.