DeepSeek V4 Pro 0813

336

eexplosion-s about 3 hours ago 111 commentsRead Article on openrouter.ai

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Discussion Sentiment

75% Positive

Analyzed from 3234 words in the discussion.

Discussion (111 Comments)Read Original on HackerNews

freakynit•28 minutes ago

Just tested through openrouter.. gave exactly same task.. the task was to scan existing repo, and generate a single docker-compose file to deploy behind a caddy server, where certain port ranges are already used, the service demands widlcard certificates to be provisioned from outside, and postgre needs to be built-in one...

Tested this model, and gpt-5.6-terra-high.

Results: this one had few issues. terra: none.

These results are consistent with my past observations with the latest flash version as well. What benchmarks say, vs what I've been observing are different.

They are good till the project is simple... not anymore.

derangedHorse•7 minutes ago

Terra has not been able to do any of the technical tasks I've asked of it correctly. I'm surprised others get use out of it. Anything below Sol high tends to give me mostly unreliable results. I'm using codex as my main harness but maybe it performs better with a different one.

freakynit•5 minutes ago

Depends on project complexity. For one of my more complex projects, I exclusively use sol-high ... nothing below that works correctly.

For this however, a comparatively much simpler task, tarra-high works fine.

npn•14 minutes ago

wait for Deepseek Harness (yes it is the official name) release then try again.

for your kind of task, harness tools matter.

gkbrk•6 minutes ago

If the model cannot figure out simple and ubiquitous tools, how is it supposed to figure out complex problems? All of the good models basically work with any harness, including giving them a single "shell command" tool. They can just figure things out.

sheeshkebab•less than a minute ago

This. The same goes for “skills”, skill type “subagents” and other bullshit - powerful models don’t need any of that anymore I noticed.

hadlock•2 minutes ago

When it comes to quality of outcome, since at least Feburary, the harness has almost equal, if not more weight than the model itself. It's no longer "which model is the best?" it's "which model + harness is the best?"

I get drastically different tool call failure rates using Claude SDK vs OpenCode using Qwen 3.6 models

freakynit•8 minutes ago

I used pi

scrlk•10 minutes ago

What harness are you using? DS V4 is harness sensitive.

lousken•3 minutes ago

Are we testing the model or the harness? If benchmarks show certain numbers it should perform as such without it

freakynit•9 minutes ago

shimman•19 minutes ago

I've always wondered if I was using containers wrong because none of them I've ever had to create were complicated. Maybe it's because I choose tools that make local development easy (Go + sqlite + various CLTs) or maybe it's because I never hard to interact with this on the professional side outside of making images for our projects (which still weren't complicated for the reasons above).

LLMs make containers in a pretty workable format for me (still hand tweak the env variables for a sanity check).

How exactly does it struggle here and why does postgres need to be built? Were the needs beyond what you get in a base image?

freakynit•12 minutes ago

This was the repo: https://github.com/amalshaji/portr

And this was my gh issue: https://github.com/amalshaji/portr/issues/308

And below was my prompt:

""" give me single docker-compose file that i can run on my server to run current project... you can read README.md , and then, this relevant page: https://docs-custom-reverse-proxy.portr-docs.pages.dev/docs/... ... this was the result of me raising github issue: https://github.com/amalshaji/portr/issues/308 ... you can use gh cli to fetch the details and comments...

i already have a caddy server running on my vps... and i will create wildcard certificates myself using certbot.. the domain name will be helloportr.xyz ... also, ports up to 9019 are already taken...

ask me if anymore info is needed... """

You can try yourself and let me know of what you got.

scrlk•about 2 hours ago

Benchmarks:

    | Benchmark                | DS-V4-Pro | DS-V4-Flash | DS-V4-Pro | DS-V4-Flash | GLM-5.2   | Kimi-K3   | Opus-4.8  | Fable 5       |
    |                          | 0813      | 0731        | Preview   | Preview     |           |           |           | (w/ fallback) |
    |--------------------------|-----------|-------------|-----------|-------------|-----------|-----------|-----------|---------------|
    | HLE (wo/w tools)         | 42.7/60.0 | 37.8/51.5   | 37.7/48.2 | 34.8/45.1   | 40.5/54.7 | 43.5/56.0 | 49.8/57.9 | 53.3/63.0     |
    | Terminal Bench 2.1       | 87.9      | 82.7        | 72.1      | 61.8        | 81.0      | 88.3      | 85.0      | 88.0          |
    | NL2Repo                  | 61.5      | 54.2        | 38.5      | 39.4        | 48.9      | -         | 69.7      | -             |
    | Cybergym                 | 83.3      | 76.7        | 52.7      | 38.7        | -         | 80.0      | 78.3      | 83.1          |
    | DeepSWE                  | 62.7      | 54.4        | 12.8      | 7.3         | 46.2      | 67.5      | 58.0      | 70.0          |
    | Toolathlon-Verified      | 74.1      | 70.3        | 55.9      | 49.7        | 59.9      | 76.5      | 76.2      | 77.9          |
    | Agents' Last Exam        | 25.7      | 25.2        | 16.5      | 15.8        | 23.8      | 27.6      | 25.7      | -             |
    | AutomationBench (Public) | 31.8      | 25.1        | 12.8      | 10.8        | 12.9      | 30.8      | 27.2      | 29.1          |
    | DSBench-FullStack        | 71.1      | 68.7        | 41.8      | 37.0        | 61.8      | 73.7      | 71.6      | 77.2          |
    | DSBench-Hard             | 67.2      | 59.6        | 31.1      | 25.8        | 54.5      | 63.0      | 71.7      | 68.3          |

Source: https://reddit.com/r/LocalLLaMA/comments/1vmi0fg/deepseek_v4...

parsimo2010•about 2 hours ago

The timing looks like they are trying to take the wind out of Qwen's sails by releasing this on the same day that Qwen released the weights of Qwen3.8-max. Or maybe it's coincidence...

For comparison I looked at Qwen's claimed benchmarks for Qwen3.8-max (https://qwen.ai/blog?id=qwen3.8). Assuming each published set of benchmarks is believable, it looks like v4 Pro 0813 is better on average but overall performance is comparable. Pro 0813 is much cheaper. If you don't need vision capabilities then you don't have much reason to use Qwen3.8-max.

- 43.6 on HLE (Presumably without tools). Pro 0813 is a little worse.

- 86.6 on Terminal Bench 2.1. Pro 0813 is better.

- 55.9 on NL2Repo. Pro 0813 is better.

- 27 on Agent's Last Exam. Pro 0813 is a little worse.

- 72.5 on Toolathon-Verified. Pro 0813 is better.

- 56.6 on DeepSWE 1.1. If the DeepSWE listed for Pro 0813 is the same version, then Pro is better.

- 27.3 on AutomationBench. If the AutomationBench (Public) listed for Pro 0813 is the same, then Pro is better.

I guess we do need to wait to see if the upcoming DS pricing increase is enough to change the value proposition. As it is now, they could double or triple prices and it still would be a better value to use DS. I bet they know that.

trollbridge•about 1 hour ago

By that standard, the release of Grok 4.6 was also timed on the same day.

Given how I think DeepSeek operates... I think they just release it when they feel it's ready, and don't even seem that concerned with what other people are doing.

somenameforme•about 1 hour ago

Their leaks would confirm this sort of attitude. They're not trying to become the top player or anything like that - just working to play their part in pushing LLM tech forward and going from there. It was quite refreshing from the 'here's how we're going to dominate the world' nonsense. It's undoubtedly the same attitude that just lets them shrug and cancel the fund raising round after the leaks came from said funding round.

parsimo2010•about 1 hour ago

Actually, yes. I just didn't know about Grok's release because they aren't on the front page of HN.

eli•about 1 hour ago

Official pricing only kinda matters for an open weight model, no?

parsimo2010•about 1 hour ago

It still matters as a point of comparison until other providers come online. If the consensus price from other providers is much different that can be compared then. But for now we have $0.435 / $0.87 for v4 Pro 0813 (with increase announced but we don't know the new pricing), and $2 / $6 for Qwen3.8-max. So until we get other data points that is what we have to look at.

maherbeg•about 1 hour ago

I mean at the rate of model releases happening, I think a lot of these will collide more often than expected!

goldenarm•about 1 hour ago

Geometric mean of all these benchmarks :

* GPT-5.6 Sol: 65.5

* Fable 5 (w/ fallback): 64.5

* Opus 5: 64.0

* DS-V4-Pro 0813: 62.5

* Kimi-K3: 62.3

* DS-V4-Flash 0731: 55.8

* GLM-5.2: 47.3

svachalek•about 1 hour ago

Maybe it's me but I don't see how DS Flash is better than GLM at all, much less by a huge gap. I'd probably protest less against Fable and Opus being put at the same level than many would, but there's no denying the two models are a very different experience from each other. I guess where I'm going is no one should pick a model by the benchmarks.

spijdar•4 minutes ago

I'm not the most LLM-savvy person around, and I'm not gonna say I've put a ton of effort into practically compared these open models. But, a month or two ago I did do some "practical evaluates" testing GLM 5.2 versus DSv4 (flash/pro) with OpenCode's subscription with some late 80s Unix clone-type work, and this jives with my experience.

GLM ended up being far slower, and far more expensive, for approximately the same results. There was never a problem that GLM could solve that DS couldn't solve, faster, and significantly cheaper.

I strongly agree that you shouldn't pick a model based on benchmarks. But for me, I found GLM really underwhelming given its cost and speed.

DSv4 isn't as good as GPT or Claude or what have you, but it's fast, and pretty darned effective. I can run a 3-bit quant of DSv4 locally on my system with ~15 tokens per second, and for a local model it might be the most overall effective at coding. For what it is, it's extremely impressive.

platinumrad•27 minutes ago

I think instruction following carries outsized weight in these evaluations.

bel8•about 1 hour ago

So it's a Fable class LLM?

                             DSV4Pro vs Fable5
    HLE w tools              60.0 vs 63.0
    Terminal Bench 2.1       87.9 vs 88.0
    Cybergym                 83.3 vs 83.1
    DeepSWE                  62.7 vs 70.0
    Toolathlon-Verified      74.1 vs 77.9
    AutomationBench (Public) 31.8 vs 29.1
    DSBench-FullStack        71.1 vs 77.2
    DSBench-Hard             67.2 vs 68.3

eli•about 1 hour ago

Fable's guardrails would never let it do something like Cybergym so at least for that one it's measuring Opus 5

wren6991•about 1 hour ago

We have a first-party figure from the system card [1]:

> Mythos 5 reproduced 83.8% of targeted vulnerabilities on a single try, and produced at least one crash in 99.4% of tasks. This is comparable to Claude Mythos Preview, which reproduced 83.1% of targeted vulnerabilities and produced a crash in 97.1% of tasks. By contrast, Claude Opus 4.8 achieved a score of 78.1% (95.7% any crash).

So their quoted figure exactly matches the figure for Mythos Preview, although they don't state the provenance. It could also quite possibly be an independent measurement of Opus 5.

[1]: https://www-cdn.anthropic.com/57a52ea7d8f0e54e8a542e90826608...

aftbit•about 1 hour ago

Fabble lol

NietTim•43 minutes ago

In classic reddit fashion the post you linked to is now deleted

SV_BubbleTime•36 minutes ago

To be fair… I don’t know who still needs to figure out that AI benchmarks are almost all entirely fucking trash, but the great number would surely surprise me.

jklmnopqrstuvw•about 1 hour ago

Tested both DS v4 pro 0813 and Grok 4.6 (all from openrouter) on Codex cli. Worked on a same new feature development on my project.

Deepseek 4 pro: Worked for 12m 02s - cost $0.12 - has bug.

Grok 4.6: Worked for 3m 18s - cost $ 1.41 - no bug.

computerex•about 1 hour ago

Repeat the test like 5 times for each model and see the results.

epolanski•about 1 hour ago

+1, a single test means little.

jklmnopqrstuvw•41 minutes ago

I don't think so. I specifically kept this PR to test model capabilities, and I've already tested a bunch of models. Current test results show that the more advanced the model is, the easier it passes. For example, GPT-5.5 Medium fails the test(has bug), but High passed.

ferongr•about 1 hour ago

Rocket man bad.

nozzlegear•about 1 hour ago

This but unironically

SV_BubbleTime•30 minutes ago

So.. flesh this out and don’t be a coward about it.

You are saying that the products made by thousands of people are to be shit on and hidden away from discussion because you don’t like a guy in charge? That the quality and performance of the product is second tier to collective-take culture war considerations, real or mostly make believe? That only the things made by “The Good Ones” are to be discussed because of righteousness? Is it because if Rocket Man Bad, but Rocket Man Products Good, that would cost you legitimacy in the first part?

And you assert that while daring to talk about irony?

numpad0•42 minutes ago

no he and his stuffs are now considered transparent, no pun intended. I think he deserves it since his minions were persistent with usage of "this ___ has hateful bias against ___" canned response.

Zetaphor•20 minutes ago

It's the third link on the front page right now?

NooneAtAll3•37 minutes ago

I thought it was impossible to downvote posts?

aabdi•about 3 hours ago

https://api-docs.deepseek.com/quick_start/pricing/

Competitive with opus 4.8 but weaker than sol or fable. About 20x cheaper.

xynelius•about 1 hour ago

If that wasn't impressive enough, it's actually ~60x cheaper if you take into account the typical cache-read/input/output split in agentic coding, and the deep discount for cache reads offered by DeepSeek. Opencode has some public data on the typical split [1]:

For DeepSeek V4 Pro the typical split is 750 in, 290 out, 82k cached.

Cost per request for V4 Pro: $0.000875 per request.

Equivalent Opus cost (w/o taking into account cache write costs): $0.052 per request.

[1] https://opencode.ai/docs/go/#usage-limits

JacobAsmuth•about 2 hours ago

Per token. You need to look at pricing per task.

trollbridge•about 1 hour ago

... which still comes out cheaper, since DeepSeek caches so much more.

I keep track of my token consumption even on subscription plans and my equiv. cost for my 5.6-Sol usage is around $4000-$8000 a month.

swiftcoder•about 2 hours ago

How does it stack against the updated Deepseek Flash version?

pixelesque•about 2 hours ago

I've found Pro to be a lot better per "task" than the recently released Flash for code reviews and things (via OpenRouter running in pi.dev).

Flash makes a lot more initial mistakes, and then has to re-check stuff, and produces much more output compared to Pro. It often gets to the correct result eventually, but the output volume is often 5x more than for Pro, and the initial outputs are often wrong, with the first few saying something wrong (like there's a bug, or the code won't compile when it does), and then saying things like "Wait, let me re-check:", or "Actually, looking at it more carefully:" and then it thinks a bit more and eventually gets to the right answer.

swiftcoder•about 2 hours ago

yeah, I've definitely noticed one has to be quite precise to keep Flash on the straight-and-narrow

surgical_fire•about 1 hour ago

I use a plan -> implement wotkflow for this reason.

pro plans, flash implements. I am super happy with how flash behaves like that.

k__•about 2 hours ago

Around 5 percentage points better. (E.g., 87% instead of 82%)

Gecko4072•about 2 hours ago

So not worth it over flash? Even at ~7x the size it isn't worth the price hike. Flash may be a monster of a model due to all the RL it received from free usage everywhere.

sparkling•about 2 hours ago

deepseek-v4-flash feels so fast and snappy, i'm loving it. Happy to trade speed for the the 5% degraded benchmarking performance.

alecsm•about 1 hour ago

I've been using the last Deepseek Flash update for a week and I'm amazed. It was a capable model for easy tasks but now it looks like it can do some heavy development for peanuts.

I can't wait to try this new one.

coredog64•40 minutes ago

IME I can't trust it to write it's own plans from a spec, but if I give it a detailed execution plan written by Opus, it's fast and cheap (if chatty) in executing it.

xnyan•20 minutes ago

I find DeepSeek flash incredible for the price and good in general if it has good plans. I will typically plan using Opus or GLM, then implement with DSF

Gecko4072•about 2 hours ago

Currently burning money quickly on official deepseek api. They are also increasing pricing starting today. V4 Flash 0731 still feels like the most outstanding model of the past few months and probably to come.

nolist_policy•about 2 hours ago

DeepSeek V4 Flash is the "too cheap to meter" of AI. And you can run the full unquantized model locally for $8000 (2x DGX Spark) at full 1M context and decent speeds: https://github.com/elsung/dgx-spark-deepseek-v4-flash#-long-...

sschueller•about 1 hour ago

Deepseek seems to have gotten too cheap. I have been using it for a long time and it's at a point now where my credits balance barely moves even at max setting.

eli•about 1 hour ago

The Deepseek official API is good with excellent caching.

But their privacy policy is unusually bad - they can train off your prompts and completions.

trollbridge•32 minutes ago

Use another provider from OpenRouter.

I really don’t care if they train off my prompts.

Eueudhsbsj32•about 2 hours ago

What's the new pricing?

The prices on OpenRouter still look the same.

igravious•about 2 hours ago

yup :)

i'm doing opencode <-> openrouter <-> official deepseek api (i don't get the opencode hate, i like it)

how are you doing it?

am also using Kimi K3 via kimi-code

and also GLM 5.2 via ZCode

happy with all three, they're trailing frontier but i figure if i'm running GNU/Linux then i ought to favour open weights models with my €s -- reduced my usage of claude/gpt to the ~$20 tier just to keep abreast of claude_code/codex developments

literallyroy•25 minutes ago

> i don't get the opencode hate, i like it

When the company I work for was evaluating it, there were multiple rough points. Their terms and conditions allowed training on prompts, the default behavior was to route prompts to their servers for conversation summary/labeling. One of their lead maintainers is also super toxic on many issues.

Sorry this is all baseless with no links, I’m on my phone and locating those issues again isn’t something I have time for.

It’s a good tool I just don’t like the privacy policies nor maintainers attitudes.

Jsttan•about 2 hours ago

What is the new price through?

Gecko4072•about 2 hours ago

https://api-docs.deepseek.com/quick_start/pricing/

edit: there are banner announcements saying v4 flash pricing will increase first then overall by an undetermined amount

nchmy•about 2 hours ago

i dont see any price increase there... what am i missing?

minraws•about 2 hours ago

isn't it the same old pricing? did they increase V4 Pro pricing already?

indigodaddy•about 2 hours ago

@dang - Pls merge this with https://news.ycombinator.com/item?id=49274018

CharlesW•22 minutes ago

Email hn@ycombinator.com with anything you want HN mods to see. They're incredibly responsive.

eshack94•about 1 hour ago

It appears that the only available endpoint (as of this writing) requires enabling "Allow paid endpoints that train on request data" in the OpenRouter privacy settings. I hope additional paid providers will become available that don't require training on data.

jubilanti•about 1 hour ago

Their privacy policy doesn't forbid them from just straight up publishing your raw prompts as training data.

My threat model is that anything I POST to DeepSeek I treat as public to the web, as much as a public GitHub repo is.

cdolan•about 1 hour ago

That is likely because Deepseek themselves is the only host.

In 24-48 hours there will be other options I presume

book_mike•about 2 hours ago

What I care about is whether the model is capable of the tasks I give it at the lowest cost. Right now I'm using Kimi-K3/GLM-5.2/Minimax. Sonnet is great but I burn through the tokens too fast. Opus 5 set to max is amazing and more intelligent than all of us. .998 of the time I don't need that kind of intelligence. I just need the job done.

okamiueru•about 1 hour ago

How do you define intelligence? I encounter that kind of sentiment all too often, and I have to assume we go by wildly different understanding of what that might entail.

bikemike026•about 1 hour ago

If you read Opus 5's output, it is beyond the comprehension of virtually all engineers and developers. That is what I mean by intelligence. Math, science, and engineering are all contained in one model. We may be experts in one field. The model is an expert in everything that humans know.

okamiueru•32 minutes ago

I'd have to ask for you to be more specific, otherwise, to take your answer at face value, it comes across as a contradiction.

> [Opus 5's output] is beyond the comprehension of virtually all engineers and developers

That would make it pretty bad? The key defining quality of good software, is clarity, and the ability to simplify a complex problem to the point of it seeming trivial.

> Math, science, and engineering are all contained in one model. We may be experts in one field. The model is an expert in everything that humans know.

The bar here should absolutely be to judge this against the expert level within each domain. I have time and time come across LLM output being woefully underwhelming in every single request where I am an expert. For all areas that I am not, it sure seems plausible. It is far more likely than not, that it is equally inadequate in the areas I lack the necessary knowledge to tell.

If the AI is being subpar in every field and category compared to an expert in said respective field, then, what a strange gauge of a tool's usefulness. Are we attributing higher value because a single model is "attempting to solve all knowledge and fields at the same time", why is that of any importance, or excuse?

We should not define "intelligence" as how effectively it can convince a non-expert of something being plausible. That sounds like the absolute worst tradeoff. You'd have to waste the experts time in filtering and refuting incorrect postulations that are cheep to generate. The perfect storm for bullshit asymmetry.

hgoel•32 minutes ago

I don't think that's because of its "intelligence". It speaks obtuse techbro-ese: stringing together words that sound smart to obscure the simplicity of the thing it's describing. In many ways it's the opposite of intelligence.

Opus 5 and Fable 5 in particular suffer from this issue at worse level than most models in the same class.

logicchains•33 minutes ago

You mean Fable 5 right? Opus 5 makes lots of stupid mistakes about anything that requires any domain knowledge.

nullbyte•about 1 hour ago

Even though cost-per-token is low, Deepseek v4 tends to burn an immense number of tokens to accomplish tasks.

Readerium•about 1 hour ago

V4 Pro has vision correct?

trollbridge•about 1 hour ago

No.

coredog64•38 minutes ago

Saw somewhere that they don't believe vision advances the AGI work they're doing, so it's not on the roadmap.

nthypes•about 1 hour ago

Still behind Kimi-K3 in almost half of the benchmarks

LeonKnst•about 2 hours ago

I find it interesting how much adoption seems to be influenced by momentum. Some of these Chinese models are surprisingly capable, but developers often default to the models that are already established as the “industry standard

krlx•about 1 hour ago

Well things may change soon. I've been testing Coding fulltime with Deepseek Flash this week to evaluate an eventual shift for the whole company away from anthropic. It has been quite positive and I can't wait to try pro tomorrow. If our data has to be used by either US or China, we might as well go the cheaper and unwalled garden. If only it supported image input ...

numpad0•25 minutes ago

There's just no place for models that are neither SoTA nor truly crazy cheap in today's public mental health climate.

If it's 500x cheaper than US models for similar ballpark performance just because it's hosted in China, sure whatever. If it's name brand like Anthropic/OpenAI/Google, that's kinda fine too.

If it's neither, like merely 50% cheaper than latest OpenAI whatever, however massive loss that pricing may be incurring to its provider, it wpuld be considered not worth any attention.

sinuhe69•about 2 hours ago

Well, one reason is that we always have to work with the quirks of each model. So, a know model is often preferred over a new/unknown one because we have to be vigilant again. (Negative) surprises are mentally exhausting in the long run. IMO, you can work much better when you know the model.

spacebanana7•about 2 hours ago

In an enterprise setting Chinese models are often discouraged due to political risk. They don't want to need to remove a model that's deeply embedded in their stack. And it's entirely feasible that the US gov bans federal contractors from using them in the next 6 months for example, or that EU AI safety rules effectively ban them too.

BlackRabbit1•about 1 hour ago

There are EU/US providers offering Deepseek/Qwen/Kimi/etc.-as-a-Service. With zero ties of their infrastructure to China.

Fully compatible with the well known Antrophic API.

You only have to replace the URL and your key.

odo1242•about 1 hour ago

Based on what the political climate looks like nowadays it's entirely possible the US bans federal contractors from associating with any company that uses the models themselves, regardless of data provenance or where they are hosted. Or they create AI safety rules that make it impossible to release open source models (for example, making it so that closed-source models can be evaluated with a harness but open-source models need to pass the benchmark with the weights alone, which isn't really possible). Or they just declare Chinese models a security risk like TikTok (claiming that the model would be trained to respect Chinese interests).

It may not be likely but it's definitely possible enough to be something people worry about.

trollbridge•about 1 hour ago

Then run the DeepSeek or Qwen model on AWS GovCloud, etc., and you won't have any risk of exposure to "China".

I'm not even sure what "EU AI safety rules" are. Can't people in the EU just use whatever they want?

hgoel•27 minutes ago

Running on AWS GovCloud isn't necessarily an option, some places prohibit running Chinese origin models even locally.

cortesoft•33 minutes ago

I keep using Claude and Codex simply because the subscription rates are SO MUCH cheaper than per-token rates, even with the cheaper models

HawtAds•about 2 hours ago

Hacker News is very Bay Area/US tech centric where spending a few hundred a month on AI is just pocket change. The weaker AI models with more questionable data retention policies are popular in developing countries. I think the new Facebook muse model will be similarly popular.

ianm218•about 1 hour ago

I suspect if you follow dev groups in developing countries people are much more focused on token/ price efficiency.

For funded startups it mostly just doesn’t matter a ton unless you are passing on inference in your product at scale

BlackRabbit1•about 2 hours ago

A lot of it/infrastructure departments aren't aware that you can use Asian models hosted within the US or even EU.

spacephysics•about 1 hour ago

Most of my model usage comes from my work’s model selection (which is now down to just Claude models)

I’ll try out the latest models, but mainly stick with Claude only because I’m most used to its quirks and how to work around them. I imagine this is part of these hyperscalers playbook.

I will say though, I miss Sol model at work. It with Codex was amazing at first-shot understanding. Claude i need to scope out where to look otherwise a large portion of my token budget is eaten up

yipinwong•about 1 hour ago

Worse than Luna but more expensive than Luna. Sticking with Luna without sending my data to Deepseek (China)

Eueudhsbsj32•about 1 hour ago

Unless you're Chinese, why would you care if they see your data?

As an American, I'd much rather have my data kept outside the country than here where companies and the government have a lot more leverage over me.

iammrpayments•27 minutes ago

It’s either chinese in the US or chinese in China anyway