Earlier quoted context omitted.
What does it mean, if it is American? Is it censored or will it eventually stop working in Middle Eastern countries? Or is it biased towards powerful political lobby group interests? When weights are open I usually don't care where is it from, as long as it is working for my use cases well
There's a lot of Sinophobia in the tech world, and the AI race seems to be magnifying that. With very little evidence to back it up, I might add - we've had regular releases of quality open-weight models from Chinese firms, and no sign they are more censored/ideological, than, say, Grok
Inkling: Our Open-Weights Model
311–320 of 324 posts
Re: Inkling: Our Open-Weights Model
#312Earlier quoted context omitted.
What does it mean, if it is American? Is it censored or will it eventually stop working in Middle Eastern countries? Or is it biased towards powerful political lobby group interests? When weights are open I usually don't care where is it from, as long as it is working for my use cases well
There's a lot of Sinophobia in the tech world, and the AI race seems to be magnifying that. With very little evidence to back it up, I might add - we've had regular releases of quality open-weight models from Chinese firms, and no sign they are more censored/ideological, than, say, Grok
Re: Inkling: Our Open-Weights Model
#313Earlier quoted context omitted.
DS3 isn't even looked at anymore. GLM-5.2 is the best in that class right now. It is competitive with current GPT/Claude/Gemini.
"Current GPT/Claude/Gemini" is not a meaningful statement about perf. There's many different models from each of those providers and there's a considerable gap between the best of anthropic and open ai compared to gemini. Benchmarks have GLM 5.2 somewhere underneath Sol and Fable and closer to now last-gen openai and anthropic models.
Newly released Kimi K3 is benching better than Claude Opus 4.8. The only better models are Claude Fable and GPT 5.6 Sol Max Effort.
Re: Inkling: Our Open-Weights Model
#314Earlier quoted context omitted.
"Current GPT/Claude/Gemini" is not a meaningful statement about perf. There's many different models from each of those providers and there's a considerable gap between the best of anthropic and open ai compared to gemini. Benchmarks have GLM 5.2 somewhere underneath Sol and Fable and closer to now last-gen openai and anthropic models.
One error: GLM 5.2 beats the best public Gemini model, 3.5 pro. There's 2 caveats with the rest. First, GLM 5.2 matches those models in "xhigh" effort modes, which has a very low quota on the subscriptions, especially for Claude. Second, last-gen GPT/Claude means what they release in April/May of 2026. Or to be even more complete/fair: GLM 5.2 beats what OpenAI released in March 2026 (GPT 5.5 xxhigh), and what Anthro…
Opus 4.8 (May) to Kimi K3 (July) has apparently just dropped it to two months.
China also does efficiency improvements. Qwen 3.6 27B is better than Sonnet 4.5 and you can run it on a couple of gaming video cards. That's incredible. I can do real actual work with this!
As Google said in 2023, none of them have a moat, open weight models will win.
Re: Inkling: Our Open-Weights Model
#315Earlier quoted context omitted.
Cf Microsoft v Intel circa 1995
Usually software wins over hardware, but the voracious appetite of LLMs has inverted the usual balance of power.
Re: Inkling: Our Open-Weights Model
#316Re: Inkling: Our Open-Weights Model
#317America needs its own DeepSeek or Z.ai, a lot of people (myself included) root for open chinese models to win because they have no other choice. Thinking Machines might be it.
What does "winning" mean to you?
Re: Inkling: Our Open-Weights Model
#318This is a winner IMO. Lots of cost pressure on token spend atm within enterprises and tasks that don't require Opus / Codex class models. These companies have hopefully captured all of their traces and now have enough to fine-tune an open model and host themselves. Inkling feels like the right base - not obsessed with benchmaxxing on coding but rather being adaptable to the task required For tasks like GTM, support,…
Can chime in on the support use case specifically: GPT OSS performs really well here and has been somewhat of a benchmark with our customers, limited testing [0] against Inkling reveals basically identical performance, but with a significant cost increase at scale.
I'd say that for real-world tasks that aren't coding most companies don't see value by being on the latest and greatest model.
[0] https://valiopt.com/blog/inkling-model-customer-support-revi...
Re: Inkling: Our Open-Weights Model
#319Earlier quoted context omitted.
MiniMax M3 and DeepSeek v4-Pro are highly capable long context open weight multi-modal models. But long-context is a trap, because performance still falls dramatically after 150k-200k context.
> But long-context is a trap, because performance still falls dramatically after 150k-200k context. I'm not sure exactly what causes the difference, but this heavily depends on the model. In my experience with Opus 4.8, I can go well over 500k and still get extremely good results. A drastically different example was GLM-5.1, which worked great until about 100k and then turned insane almost immediately. They did fix t…
Re: Inkling: Our Open-Weights Model
#320Earlier quoted context omitted.
MiniMax M3 and DeepSeek v4-Pro are highly capable long context open weight multi-modal models. But long-context is a trap, because performance still falls dramatically after 150k-200k context.
> But long-context is a trap, because performance still falls dramatically after 150k-200k context. I often see this repeated, and it is not true task to task. I work on this daily and we have several tasks where long context is advantageous and our evals against a whole battery of models with different windows show it as being so. This is why having good evals for the tasks you're working on is so important. I do gr…