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Comment by jiehong | Hacker News Reader

Sounds nice!

But, the web ui chat version of flash has very poor language following abilities in my experience:

You may ask it something in English, and get a thinking chain in Chinese with an answer in Chinese, or an English thinking chain and an English answer. Using the retry button on the same question has a 50/50 chance of any of those results.

Sometimes, asking something in English, but where information are mostly in another language may make the answer in the language where data has been found. The other day, I asked something about a local German thing, in English, and I got an answer in German instead. It’s as if all the language data stirred it away from the language of the user’s question.

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It's not just web chat, V4 Flash 7/31 suffers from a lot of pathological behavior in coding harnesses as well, e.g. infinite loops, hallucinations, premature termination, and invalid tool calls.

FWIW, I haven’t experienced any of that using V4 Flash via DeepSeek in omp. What’s your coding harness and inference provider?

Same. My side projects are coded almost exclusively with the Deepseek V4 Flash 07/31 in omp, and it recovers beautifully in every case. I'm using OpenCode Zen.

OpenCode but I variously use DeepSeek API/OpenRouter/Vercel AI gateway. I'm sure it's the combo of model + inference provider that is the issue and not the model alone. DeepSeek API also has far better inference speed and reliability than the cheapest providers. That said I never seem to have these issues when using GLM 5.3 flash served by OpenRouter/Vercel.

This never happens on the deepseek api. It’s always a different provider using lower quants.

All of these flash models have this. You have to build your harness so that it deals with it. Infinite loops are solved by having an error message that says what to do differently on failure, invalid tool calls are solved by making the tool schema less strict and detect things in the runtime etc.

Hallucinations you can't fix. Gemini is a bit worse there than DeepSeek, but there's not much research on how to fix that. The only one is the CaMeL paper by Google, where you tag every prompt and result and then for every assistant response or tool call you first check where it got that data and error if you notice fabrication. This one is really annoying to implement.

With larger models the fabrication starts when the context grows or if you have too many tools, for flash models it's much earlier. We use the flash models for repetitive agentic tasks, where the prompt defines clearly what to do and how. The whole run is about 4-5 steps typically, and context size stays in the comfort zone.

Can you share what tools and processes you're using to do this?

I've been using Pi to build custom extensions and wrapping workflows in shell processes to make it more deterministic and enforce certain validations, all guided by Fable. This isn't production work, though, just playing llm factorio at home.

What you want is a bunch of sessions to replay. Something anonymized if it's not yours, and something that's not depending on state.

You replay all your sessions against your harness, and then store all logs all output, everything to a safe place.

Finally use a blind judge to check everything, and score the output.

Then fix your harness, iterate again until better until you are in a point where it's just the model's weakness. If you get to that, use a bigger model.

I have used the flash model for over 3b tokens and ofc. I saw some hallucinations and premature termination (I also get this on Astra - way more often than with deepseek v4 flash), but I never had a infinite loop (using the copilot as harness).

I used a lot V4 flash to implement plans built by other models, and it was honestly top notch. The thing was a workhorse, and I got none of the isuses you describe.

I was mostly using DeepSeek on Pi, connecting to their API directly (not some third party provider).

I honestly have more issues steering Sonnet properly.

That may be an issue with the harness you are using, i've never, and never heard of, someone having this problem specifically with this model.

disagree; been using flash as my exclusive model (other contributors have used other models) to build a complicated software project, a web engine. See https://github.com/gterzian/formal-web, which as you can see comes with very specific guidance explaining how to implement features.

I'm using headless Pi with my own UI and sandbox client, https://github.com/gterzian/uni03C0, as well as a bunch of Pi extensions for things like accessing Web standards and browser use via CDP for testing.

Switching to 4.1 today...

Edit: it seems they pushed the date at which they route the Pro calls to new Flash, so today I ended up paying regular Pro rates thinking I was using the new Flash; an example of how their offering is not quite as predictable as I would like it to be (the other is cache performance being unpredictable).

There is a chrome extension that injects “respond in English” and “English [checkbox emoji]” to every query. This helps a lot but I still sometimes get Chinese responses. I have not had this issue via api on openrouter.

Yep, the same issue. I even defined a dictionary shortcut on my phone to expand aie to "Answer in English!", but every so often it takes 5 times to force it to switch to English.

Interesting though, when I ask questions in German or my native language, I rarely get Chinese answers. Looks like English is most affected.

API never answers in Chinese.

I have the same issue, sometimes.

I initially thought it was a trick, that using Chinese chars is somehow more info dense and it saves tokens to 'think' in Chinese.

But later on it became more erratic. I still wonder if token reduction would work that way.

I've hit this too, but you can just add "in English" to steer it

I finally uninstalled the app yesterday after giving it plenty of chances over several months. Yesterday, I asked it whether «DeepSeek has fixed the issue where it erroneously answers in Chinese?» and it answered in Chinese.

So you did not do what the post you replied to suggested?

This shouldn’t be a user-facing issue. The web UI should inject the account’s language setting or solve it like competitors. They’ve mentioned giving it multiple chances but it’s still not fixed.

Anthropic does the same thing but it's not problem

Oh, I’ve tried that too. It will promise to keep it in English from here on out, then switch back to Chinese after two or three exchanges. When ever it needs to do a web search, it seems to load so much Chinese text that it forgets any language instructions. Just thought my experience yesterday was more to the point. Right now the chat is absolutely hopeless.

huh. mine only does this on the first turn on a new computer. Once I've told it once it seems to be entirely sticky on that device from then on

On the contrary, this is very strong steering in a prompt!

No you can't. It still responds in Chinese after explicitly asking it to "Always reason and respond in English."

I've literally only done this once per computer I use the web interface on, and it's always stuck thereafter. I can't speak to the mobile app

All flash llms have this problems. gemini. I start to a new chat write in german and suddenly it answers in english.

I take the free chat gpt one writ with it in polish suddenly english.

You see this on Reddit where the bot accounts will just comment in German, French or Italian randomly (and other bot accounts responding to it won't even bat an eye, responding in English as if it's the most natural thing in the world)

It's a bit more complicated than that because Reddit now automatically tries to translate comments not in the user's language.

I've occasionally got chinese characters in anthropic/openai's responses too, locally on codex/claude.

Hasn't happened in a while, last time was when I was testing fable 5 in june.

I don’t know what model codex uses for session summarization (I use Pro subscription, no third party models), but I get Chinese summaries from time to time, when the only Chinese that could have appeared in the session would be an i18n strings file that it may or may not have loaded. Very puzzling. Last happened yesterday.

I'm also totally not sure why it do that, but I guess because they're searching from China and web results comeback in Chinese so the model start using that.

The web UI's system prompt is also probably in Chinese

I've been working with Pro and it's been great so far.

Yep. I faced the exact same issue. Too many times. And then just gave up.

Very odd. I've used DeepSeek heavily for some weeks, and haven't seen a single Chinese character either in its replies or its thinking. Are you using a quantified model or a different provider by any chance?

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