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oqk0tid | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | ed0c | 1,780,967,423 | First of all, thanks for your hard work.
Since I'm a french doctor, i would really like to train your model with french.. But do you have audio files to feed your rag ? | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqk0tid/ | 1,789,194,985 | batch-priority-2026-summer |
oqk421w | LocalLLaMA | 1u0q5h9 | oqk0tid | 1 | MajesticAd2862 | 1,780,968,510 | Thanks for appreciating the work! RAG is a technology not working with these type of voice model. But v2 will be multi-lingual including French, so follow us on any of the platforms or send me a DM and I'll let you know when it's online. | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqk421w/ | 1,789,194,985 | batch-priority-2026-summer |
oqk82bl | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | nuclearbananana | 1,780,969,845 | By the way I downloaded the test dataset you have under https://github.com/Omi-Health/medical-STT-eval for a personal project, but I'm not sure you're aware, it has a lot of errors.
I cleaned up one file (day1_consultation02), parakeet v2 went from 14.1% wer to 8.7%. It was very time consuming so I haven't done any m... | 8 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqk82bl/ | 1,789,194,978 | batch-priority-2026-summer |
oqk9pum | LocalLLaMA | 1u0q5h9 | oqk82bl | 1 | MajesticAd2862 | 1,780,970,393 | Thanks for letting me know. It is a different test set and not directly related to this benchmark. But please do a PR for these fixes you did. I'll have a look into it and improve it! First time I am hearing about it while having shared it for a while, so thanks! | 7 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqk9pum/ | 1,789,194,978 | batch-priority-2026-summer |
oqkaf4r | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | LocalLLaMa_reader | 1,780,970,629 | Very interesting, Parakeet is such a strong ASR model for its size, my go-to in [Handy](https://github.com/cjpais/Handy). Three questions:
1. why did you not start from Parakeet V3? or Canary? or any other model, incl Qwen? (See also further questions)
2. Anyhow, you already noted in the comments that RAG is not possi... | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqkaf4r/ | 1,789,194,985 | batch-priority-2026-summer |
oqkb5po | LocalLLaMA | 1u0q5h9 | oqk9pum | 2 | nuclearbananana | 1,780,970,882 | I'm not able to run your benchmark (the wer above was on my own) so I can't open a pr in good faith, but I'll make an issue | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqkb5po/ | 1,789,194,978 | batch-priority-2026-summer |
oqkbm6m | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | Commercial_Eagle_693 | 1,780,971,030 | Nice, sub-1B fine-tunes punching above their weight is my favorite genre. I have been working on tiny models too and what keeps surprising me is how much headroom there is once you stop treating size as the ceiling. Out of curiosity, did the 0.6B hold up on accents or noisy audio, or is the gain mostly on clean speech?... | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqkbm6m/ | 1,789,194,978 | batch-priority-2026-summer |
oqkedcd | LocalLLaMA | 1u0q5h9 | oqkaf4r | 1 | MajesticAd2862 | 1,780,971,991 | Fully agree Parakeet is a great local model. So answering your questions:
1) Basically because it runs smoothly locally and especially the MLX version runs great on Mac locally without dedicated GPU (Qwen, Canary etc don't). This was English only, and V2 would be a bit better for English only. My multi-lingual next ve... | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqkedcd/ | 1,789,194,985 | batch-priority-2026-summer |
oqketk6 | LocalLLaMA | 1u0q5h9 | oqkbm6m | 1 | MajesticAd2862 | 1,780,972,152 | Same thing here, love when small models punch above their weights (literally). I tried to diversify the dataset with adding noise and created multiple accents, so do think it is important. But still having raw real world voice datasets still is scarce and would be very valuable. I don't have metrics on clean-vs-messy,... | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqketk6/ | 1,789,194,978 | batch-priority-2026-summer |
oqkt5xt | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | bad_detectiv3 | 1,780,977,346 | Good stuff where did you find the data to fine tune the model with? | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqkt5xt/ | 1,789,194,992 | batch-priority-2026-summer |
oql07j4 | LocalLLaMA | 1u0q5h9 | oqkt5xt | 1 | MajesticAd2862 | 1,780,980,321 | That was the real challenge. Going over many sources, including Huggingface datasets. But also created filtered sets of stuff like CommonVoice. And created synthetic targeted sets with Elevenlabs and OpenAI TTS. | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oql07j4/ | 1,789,194,992 | batch-priority-2026-summer |
oqlkjah | LocalLLaMA | 1u0q5h9 | oqk9pum | 2 | PhilippeEiffel | 1,780,990,171 | From my experience, learning data quality is critical. A single error in the dataset can drastically reduce the performance because at learning phase it makes its best to memorize this wrong value. Other training data would give the right answer for this sample, but it forces to convince itself there is a small differe... | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqlkjah/ | 1,789,194,978 | batch-priority-2026-summer |
oqlst3r | LocalLLaMA | 1u0q5h9 | oqlkjah | 3 | MajesticAd2862 | 1,780,994,613 | Couldn't agree more. But just to explain, the comment is about a different Evaluation dataset which isn't related to this model nor its training. It's also quite vague about what the issue is, so curious to hear more. In the last months I haven't heard anything while has been online for a while and shared at many place... | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqlst3r/ | 1,789,194,978 | batch-priority-2026-summer |
oqm8pc9 | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | Porespellar | 1,781,002,496 | OP, are you one of the hosts of the ThursdAI podcast? I ask because I think one of those guys made something similar (Parakeet with Medical domain app) and was discussing it on last week’s episode. | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqm8pc9/ | 1,789,194,992 | batch-priority-2026-summer |
oqojwai | LocalLLaMA | 1u0q5h9 | oqm8pc9 | 1 | MajesticAd2862 | 1,781,026,773 | I am not, but thanks for introducing me to this podcast. Was it the June 4th episode? | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqojwai/ | 1,789,194,992 | batch-priority-2026-summer |
oqouzhi | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | koloved | 1,781,029,684 | Great. Thanks for the work. It would be great to add this to Handy
It seems that this model must be converted to int8 to be used in this app. | 3 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqouzhi/ | 1,789,194,985 | batch-priority-2026-summer |
oqoyfo9 | LocalLLaMA | 1u0q5h9 | oqojwai | 2 | Porespellar | 1,781,030,616 | Yes. It was the June 4th episode towards the end of the episode. | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqoyfo9/ | 1,789,194,992 | batch-priority-2026-summer |
oqp3fuv | LocalLLaMA | 1u0q5h9 | oqouzhi | 1 | koloved | 1,781,031,959 | I have added a support request for this model. If anyone is interested, let them know in the discussions.
[https://github.com/cjpais/Handy/discussions/1490](https://github.com/cjpais/Handy/discussions/1490) | 2 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqp3fuv/ | 1,789,194,985 | batch-priority-2026-summer |
oqqmzdy | LocalLLaMA | 1u0q5h9 | 1u0q5h9 | 0 | vick2djax | 1,781,048,342 | Is there any advantage this has over just using a RAG for medical knowledge? | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqqmzdy/ | 1,789,194,992 | batch-priority-2026-summer |
oqswq3q | LocalLLaMA | 1u0q5h9 | oqqmzdy | 1 | mister2d | 1,781,081,856 | The question you're asking is for a different problem.
This fine tune appears to be about on device medical transcription, not knowledge retrieval. | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqswq3q/ | 1,789,194,992 | batch-priority-2026-summer |
oqurbm3 | LocalLLaMA | 1u0q5h9 | oqqmzdy | 1 | MajesticAd2862 | 1,781,105,125 | So RAG is not something you can use with these types of speech models. You could use it some way in context with LLM based speech models, but unsure if that’s helpful. | 1 | null | /r/LocalLLaMA/comments/1u0q5h9/i_finetuned_parakeet_06b_for_medical_asr_open/oqurbm3/ | 1,789,194,992 | batch-priority-2026-summer |
oqk1i0n | LocalLLaMA | 1u0qndz | 1u0qndz | 0 | Consistent-Height-75 | 1,780,967,657 | Also Iran attacked Israel yesterday in retaliation. | 2 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk1i0n/ | 1,789,194,975 | batch-priority-2026-summer |
oqk1rwy | LocalLLaMA | 1u0qndz | 1u0qndz | 0 | hainesk | 1,780,967,747 | >Tools for Humanity, the eyeball-scanning startup co-founded by Sam Altman, is laying off employees, according to an internal email viewed by Business Insider.
>The company has [struggled to show](https://www.businessinsider.com/sam-altman-orb-eye-scanning-startup-billion-user-goal-viability-2025-11) how its iris-scan... | 8 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk1rwy/ | 1,789,194,975 | batch-priority-2026-summer |
oqk2ge6 | LocalLLaMA | 1u0qndz | oqk1i0n | 1 | HumanDrone8721 | 1,780,967,979 | RAM Prices +10% | 0 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk2ge6/ | 1,789,194,975 | batch-priority-2026-summer |
oqk3aln | LocalLLaMA | 1u0qndz | oqk1rwy | 1 | btmalon | 1,780,968,267 | Just like Tesla it’s all a shell game. Stacking fake valuations on top of fake valuations. Who’s gonna stop em? | 6 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk3aln/ | 1,789,194,975 | batch-priority-2026-summer |
oqk46w1 | LocalLLaMA | 1u0qndz | 1u0qndz | 0 | Longjumping-Bake-557 | 1,780,968,555 | Why am I supposed to care about Sam Altman's pet project in a sub about local models | 18 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk46w1/ | 1,789,194,975 | batch-priority-2026-summer |
oqk4rvt | LocalLLaMA | 1u0qndz | oqk46w1 | 1 | HumanDrone8721 | 1,780,968,757 | Is fingers twiddling waiting for Qwen-3.7, cillax dude. | -6 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk4rvt/ | 1,789,194,975 | batch-priority-2026-summer |
oqk6c3n | LocalLLaMA | 1u0qndz | oqk1rwy | 1 | buttplugs4life4me | 1,780,969,280 | Connections. Someone knows someone who sucked someone off and voilà | 1 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk6c3n/ | 1,789,194,975 | batch-priority-2026-summer |
oqk73yx | LocalLLaMA | 1u0qndz | oqk4rvt | 2 | CalligrapherFar7833 | 1,780,969,526 | Gguf when | 4 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk73yx/ | 1,789,194,975 | batch-priority-2026-summer |
oqk9u4g | LocalLLaMA | 1u0qndz | 1u0qndz | 0 | This_Maintenance_834 | 1,780,970,433 | it is funny that he leads the company that destroyed his pet project. AI grabbed so much attention and money from the crypto world. If it wasn’t all the AI stuff, his pet project might had been doing fine. | 1 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqk9u4g/ | 1,789,194,975 | batch-priority-2026-summer |
oqka6qo | LocalLLaMA | 1u0qndz | 1u0qndz | 0 | vulcan4d | 1,780,970,550 | Oh well, at least he still owns many data centers. One sucks as much juice as the city of London and employs only enough workers to staff a Walmart. | 1 | null | /r/LocalLLaMA/comments/1u0qndz/sam_altmans_eyescanning_startup_lays_off_staff/oqka6qo/ | 1,789,194,975 | batch-priority-2026-summer |
oqk9g1y | LocalLLaMA | 1u0rqbv | 1u0rqbv | 0 | AutoModerator | 1,780,970,302 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | false | /r/LocalLLaMA/comments/1u0rqbv/deleted_by_user/oqk9g1y/ | 1,789,194,978 | batch-priority-2026-summer |
oqka5ga | LocalLLaMA | 1u0rtjm | 1u0rtjm | 0 | AutoModerator | 1,780,970,538 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | false | https://www.reddit.com/r/LocalLLaMA/comments/1u0rtjm/deleted_by_user/oqka5ga/ | 1,789,194,982 | batch-priority-2026-summer |
oqkju9x | LocalLLaMA | 1u0snw6 | 1u0snw6 | 0 | FoxiPanda | 1,780,973,908 | I'm not going to turn down some free performance on my Mac Studios... especially prompt processing. This is great! | 1 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/oqkju9x/ | 1,789,194,982 | batch-priority-2026-summer |
oqkmlhe | LocalLLaMA | 1u0snw6 | 1u0snw6 | 0 | JaredsBored | 1,780,974,888 | It's awesome to git pull, rebuild, and see a big performance bump. I'm seeing 10-15% higher prompt processing on qwen 35b and 122b on an AMD V620. That brings things almost in line with q4\_0/q4\_1 quants, impressive stuff. | 4 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/oqkmlhe/ | 1,789,194,982 | batch-priority-2026-summer |
oqkpkc8 | LocalLLaMA | 1u0snw6 | 1u0snw6 | 0 | kinetic_energy28 | 1,780,975,972 | When I first read it I was impressed, but later on I found that it is for WebGPU backend 😄 | 25 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/oqkpkc8/ | 1,789,194,982 | batch-priority-2026-summer |
oqkpu6n | LocalLLaMA | 1u0snw6 | oqkpkc8 | 1 | FoxiPanda | 1,780,976,071 | Yeah I'm less impressed now too, but hey, performance is performance. Happy for those who can use it. | 8 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/oqkpu6n/ | 1,789,194,982 | batch-priority-2026-summer |
oqkxkcx | LocalLLaMA | 1u0snw6 | oqkpkc8 | 1 | pmttyji | 1,780,979,167 | 😄 Thought the title was enough. Next time onwards, I'll include \[{Backend} Only\] in bold text
**EDIT**: Sharing another (**Open**) PR on pp which you would like to have instantly. This week or this month probably
[https://github.com/ggml-org/llama.cpp/pull/21067](https://github.com/ggml-org/llama.cpp/pull/21067) | 2 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/oqkxkcx/ | 1,789,194,982 | batch-priority-2026-summer |
ov8q0g3 | LocalLLaMA | 1u0snw6 | 1u0snw6 | 0 | crantob | 1,783,045,424 | It hurts my soul to see such workloads being shunted through a web browser. | 1 | null | /r/LocalLLaMA/comments/1u0snw6/ggmlwebgpu_improve_prefill_speeds_for_kquants/ov8q0g3/ | 1,789,194,982 | batch-priority-2026-summer |
oqkwd7e | LocalLLaMA | 1u0umuj | 1u0umuj | 0 | AutoModerator | 1,780,978,657 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | null | /r/LocalLLaMA/comments/1u0umuj/has_anyone_tried_gemma_4_qat_on_5070/oqkwd7e/ | 1,789,194,983 | batch-priority-2026-summer |
oql4plk | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | Only_Situation_4713 | 1,780,982,373 | It's not even close. Q8 is nearly indistinguishable to FP16 on any metric. Q4 with QAT is nice but not even close. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oql5uql | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | MalabaristaEnFuego | 1,780,982,907 | In my testing they're very similar and not discernible from each other in terms of accuracy. The QAT model runs 2-3x as fast, however. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oql6fyq | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | caetydid | 1,780,983,193 | I'd be happy for now to see benchmarks comparing 4-bit QAT with similar-sized q4. | 5 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlkk4d | LocalLLaMA | 1u0vltz | oql4plk | 1 | Long_comment_san | 1,780,990,183 | Got any posts or benchmarxxxs? | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlm6i0 | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | t00052e | 1,780,991,054 | I am using mlx_lm.server, prompt size around 10k using MBP M5 Max with 128Gb RAM.
8bit is 13 tok/s and 4bit QAT is 16 tok/s. 4bit no QAT is around 20 tok/s.
Not accurate benchmark, just a quick test. | -2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlnbgz | LocalLLaMA | 1u0vltz | oqlkk4d | 2 | Away-Sorbet-9740 | 1,780,991,654 | I didn't grab the links, but scrolling today I've seen the same reports popping up from people getting time to test. QAT Q4 lags behind Q6 from what I'm seeing. About to slap them in a harness and see myself though. | 5 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlo9u0 | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | we_are_mammals | 1,780,992,158 | > I'm trying to find out if anyone has done any benchmarking comparing the Gemma 4 4-bit QAT models (via Unsloth) against standard 8-bit non-QAT quants.
I have: https://www.reddit.com/r/unsloth/comments/1u0sv58/ (I'm still running some tests with Qwen3.6-27B)
The comment section has more links to other comparisons. | 13 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlpe50 | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | sfifs | 1,780,992,754 | I ran for the Gemma4 31B model yesterday a comparison on Aider Polyglot (Python and JS only) between the QAT model and NVIDIA's NVFP4 Nim image. I actually found to my surprise that there was actually a performance regression. I haven't written it up but here's the numbers. Note these are with reasoning off as reasonin... | 7 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlqm9n | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | Substantial_Step_351 | 1,780,993,420 | QAT closes most of the acurracy gap, that's the whole point of it, so on perplexity and standard accuracy you'll probably keep seeing what people report here, 4-bit QAT roughly matching the bigger quant.
The axis I'd actually want compared for agent use is different, the share of tool calls that come back as valid par... | -1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqltcr0 | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | Commercial_Eagle_693 | 1,780,994,911 | One thing I'd watch when you find a comparison: most QAT-vs-standard-quant numbers get reported as a single perplexity or a benchmark average, and that hides where the quality actually went. In my experience post-training 4-bit can hold the aggregate metrics almost perfectly while quietly degrading on the long tail, ra... | 12 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqm1yyh | LocalLLaMA | 1u0vltz | oqlpe50 | 1 | Fit-Statistician8636 | 1,780,999,411 | Off-topic but in your tests, does Qwen 3.5 122B A10B do better than Qwen3.6 27B? I have seen much more love for the latter amongst people able to run both. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqm2t69 | LocalLLaMA | 1u0vltz | oqlqm9n | 1 | IndicationUnfair7961 | 1,780,999,818 | Overall, your question is incorrect, because we don't really need to know how it compares to Standard 8bit; what we need to know is if it beats the same level quantization models like Unsloth GGUF or whatever. Ultimately, the issue is that we still need to be able to run these models on local hardware, and we need to k... | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqm3xch | LocalLLaMA | 1u0vltz | oqm1yyh | 2 | sfifs | 1,781,000,351 | Short answer yes by quite a margin especially on the more complex Aider Polyglot. My benchmarking is here - https://srinathh.medium.com/mid-size-local-models-are-now-competitive-for-ai-agents-7696b2e8b535 | 4 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqm4pn4 | LocalLLaMA | 1u0vltz | oqm3xch | 3 | Fit-Statistician8636 | 1,781,000,724 | That surprises me. Thank you. I’ll give it a chance then. (Although DSV4-Flash has proven so great it would be quite difficult to leave it even for a while.) | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqm5dbn | LocalLLaMA | 1u0vltz | oqlo9u0 | 1 | NineThreeTilNow | 1,781,001,029 | The issue with your test is your lower bound for random int my guy.
You can't claim the standard deviation solely on sample count when the tests are known to be massively different in difficulty. Even if it "averages out", the sample size to average out is massive.
If you had to test like that you'd want like... Rand... | -1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqmbjyy | LocalLLaMA | 1u0vltz | oqm5dbn | 2 | we_are_mammals | 1,781,003,687 | > You can't claim the standard deviation solely on sample count when the tests are known to be massively different in difficulty.
A real-world analogy: You have 3 different bent coins. You flip coin X to decide whether to flip coin Y or coin Z. Then you flip one of those. And that's your result. Regardless of this "s... | 4 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqmc9de | LocalLLaMA | 1u0vltz | oqm4pn4 | 4 | sfifs | 1,781,003,976 | Are you running a dual rig? DSV4 flash would not fit on a single spark for me. It is certainly superior | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqmitop | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | KURD_1_STAN | 1,781,006,487 | If u want simple 1 shot prompts video then watch tooen chaser on yt. | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqmon73 | LocalLLaMA | 1u0vltz | oqltcr0 | 1 | SkyFeistyLlama8 | 1,781,008,515 | QAT Q4_0 is much less likely to make stupid program-ending mistakes compared to regular Q4_0 or some dynamic special sauce thing like by Unsloth. I've seen it happen with JS and Python code. | -1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqmq0sq | LocalLLaMA | 1u0vltz | oqmon73 | 2 | Commercial_Eagle_693 | 1,781,008,971 | Yeah, and code is the cleanest place to see it because the failure is binary. QAT saw the quantization noise during training, so it learned to protect the brittle paths instead of smearing the error evenly across everything. Regular Q4\_0 just rounds and hopes.
The reason it stays invisible on benchmarks: a perplex... | 6 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqn1am0 | LocalLLaMA | 1u0vltz | oqmq0sq | 3 | SkyFeistyLlama8 | 1,781,012,444 | I'm talking about the 26B-A4B MOE so that model could be more prone to quantization damage than dense models.
More on long blocks of JS like making simple games with lots of animated elements or Python code with complicated classes. QAT is much less likely to make mistakes on one-shot prompts whereas regular Q4_0 made... | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqn3lic | LocalLLaMA | 1u0vltz | oqlnbgz | 3 | GoodTip7897 | 1,781,013,109 | Please post your results because we need more anecdotes and tests about this.
Google should've tested it themselves first and provided evidence but instead we're left to gather it ourselves.
I truly have no clue why qat is doing worse than q6 in my tests. Maybe the benchmarks don't capture the failure mode of reg... | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqn7y6v | LocalLLaMA | 1u0vltz | oqn1am0 | 4 | Commercial_Eagle_693 | 1,781,014,349 | The MoE detail is the key part, I think that's exactly why you saw it so hard. Q4\_0 damage isn't spread evenly across an MoE. You only need the handful of experts that actually fire for code to get rounded badly and the whole output rots. A dense model smears the error out, MoE concentrates it into the path you're usi... | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqn8zun | LocalLLaMA | 1u0vltz | oqn3lic | 4 | Away-Sorbet-9740 | 1,781,014,641 | Had a few work thing come up, but my test are largely work flow based. So we will get a peak at if it's a benchmark thing, or if it's a model thing. I grabbed a couple models, only thing I can't run well is 31B dense here at home. I'll have to put it on the work PC this week with the 4090. | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqn9ydg | LocalLLaMA | 1u0vltz | oqlm6i0 | 1 | Borilentz | 1,781,014,907 | This is not about speed but quality performance benchmarks. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqna16k | LocalLLaMA | 1u0vltz | oqn8zun | 5 | GoodTip7897 | 1,781,014,927 | Thanks.
I will be replacing qwen 3.6 27b q5_k_xl with Gemma 4 31b qat for today and seeing if it can handle the same amount of agentic work I usually throw at it.
I agree that workflow tests are much better than benchmarks. Benchmarks would suggest that Claude haiku is near the quality of qwen 3.6 27B, but my expe... | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqnd6bb | LocalLLaMA | 1u0vltz | 1u0vltz | 0 | ItilityMSP | 1,781,015,792 | You really need to run the benchmarks about five times to have any ability to compare a single run tells you nothing. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqnjhws | LocalLLaMA | 1u0vltz | oqm5dbn | 2 | audioen | 1,781,017,455 | Note that 90 % of the numbers have the maximum number of digits, because in order to have less than maximum, the first digit must be 0. This is 1/10 chance, of course. 99 % of the numbers are at most 1 digit short, for the same reason. | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqnpb2z | LocalLLaMA | 1u0vltz | oqm4pn4 | 4 | audioen | 1,781,018,944 | It is because of quantization in these results, I suspect. Any result that places 3.6-27b as roughly equally good as 3.6-35b-a3b is not correctly conducted, as there is a vast gulf between these two models in my experience. In this case, I think it is because of the ruthless NVFP4 quant of the 27b. The 27b model is not... | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqo4biz | LocalLLaMA | 1u0vltz | oqnpb2z | 5 | Choice_Celery9481 | 1,781,022,761 | have you tried unsloth version? they claimed that their q4 is much better than google provided q4 because of a bug in llama.cpp quant func | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqo4d5f | LocalLLaMA | 1u0vltz | oqnpb2z | 5 | sfifs | 1,781,022,773 | I recently ran a comparison of NVFP4 FP8 and the original BF16 on the 3.6 35b A3b model. I haven't published yet - I saw some improvements but not radically different. Aider Polyglot pass@2 came in 6-7 points higher than the quantized variants. The 122b A10B nvfp4 was 10 points higher than the BF16 of the smaller model... | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqo6stk | LocalLLaMA | 1u0vltz | oqmc9de | 5 | Fit-Statistician8636 | 1,781,023,394 | I am running FP8 27B on one RTX 6000 or BF16 on two. No difference in my benchmarks run between the two, but I prefer BF16 anyway. DSv4F FP8 can run on two with \~ 384k context with full 2x parallelism (vLLM). NVidia recently released NVFP4 - not sure how much VRAM it needs. | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqpb8ug | LocalLLaMA | 1u0vltz | oqo4d5f | 6 | Fit-Statistician8636 | 1,781,034,077 | 3.6 27B versus 3.5 122B-A10B would be interesting. As I said, people generally praise the 27B as godsend for coding, while 122B is mostly forgotten. | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqr085c | LocalLLaMA | 1u0vltz | oqm1yyh | 2 | shansoft | 1,781,052,823 | It's far superior and not even close. I been running unsloth 122B Q5 as my main go-to model. | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqr0j03 | LocalLLaMA | 1u0vltz | oqlpe50 | 1 | shansoft | 1,781,052,923 | May I ask why you prefer nvfp4 over things like unsloth q4 or q5? I find nvfp4 quality near unsloth q3 most of the time, except that it is extremely fast. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqr4pd2 | LocalLLaMA | 1u0vltz | oqn7y6v | 5 | SkyFeistyLlama8 | 1,781,054,311 | I haven't tried the QAT 26B MOE with long context jobs. It sounds like a good test to run over the weekend. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqr918p | LocalLLaMA | 1u0vltz | oqr0j03 | 2 | sfifs | 1,781,055,776 | Mainly for FLASHINFER_CUTLASS. I have a GB10 box that is in a sweet spot memory wise but bandwidth constrained, so it makes a difference for usability. | 5 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqra1xe | LocalLLaMA | 1u0vltz | oqpb8ug | 7 | sfifs | 1,781,056,117 | I did do that comparison and 27B underperforms 122b on Aider Polyglot but both tests were with NVFP4 kernels - it's in the article. If quantization has a large impact on 27B Vs the MoE models, that could explain the finding. I would have personally however expected dense models should be more resilient to quantization ... | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqreiw7 | LocalLLaMA | 1u0vltz | oqm2t69 | 2 | Substantial_Step_351 | 1,781,057,626 | Fair. The same memory comparison is the one users actually act on, 4-bit QAT against a 4-bit standard GGUF at equal footprint, not against Q8. I was answering the OP's framing, which was QAT vs 8-bit, but yours is the more useful axis I agree.
The point I'd keep either way is what you score them on. Whether it's QAT v... | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqrvv9c | LocalLLaMA | 1u0vltz | oqna16k | 6 | Away-Sorbet-9740 | 1,781,064,084 | Ok so I got some time to test and got some positive results.
#1, I'm not seeing any regression in tool calling, reasoning, or retrieval from q6/q4km when testing on 26b and 12b. 12B is actually still stronger in a few places.
#2, if you are staying all in vram memory, MTP mixed well with QAT. You get a little size ... | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
or74u2q | LocalLLaMA | 1u0vltz | oqm2t69 | 2 | Adventurous-Paper566 | 1,781,257,194 | Yes, the real question is Q4\_K\_XL vs QAT and if QAT wins then Q5\_K\_XL vs QAT. | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oulkphh | LocalLLaMA | 1u0vltz | or74u2q | 3 | IntelligentGuess42 | 1,782,774,118 | To add my small data anecdote, Q5\_K\_S beats QAT Q4\_K\_XL for two test tasks (almost single prompt) I run. | 3 | null | null | 1,789,194,981 | batch-priority-2026-summer |
ox4c6pp | LocalLLaMA | 1u0vltz | oqna16k | 6 | TomLucidor | 1,783,877,780 | Could you check if it is a template config issue? The code has been updating for a while now [https://github.com/raullenchai/Rapid-MLX/discussions/1062#discussioncomment-17598198](https://github.com/raullenchai/Rapid-MLX/discussions/1062#discussioncomment-17598198) | 1 | null | null | 1,789,194,981 | batch-priority-2026-summer |
p0yb9es | LocalLLaMA | 1u0vltz | oqmon73 | 2 | dampflokfreund | 1,785,532,205 | Try a good q4\_k quant like Q4\_K\_L by Bartowski which has imatrix. It is noticeably better than q4\_0 QAT in my experience. Less programming mistakes. | 2 | null | null | 1,789,194,981 | batch-priority-2026-summer |
oqlfjxh | LocalLLaMA | 1u0xaml | 1u0xaml | 0 | Formal-Exam-8767 | 1,780,987,623 | Was the already quantized QAT version requantized? | 0 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqlfjxh/ | 1,789,195,004 | batch-priority-2026-summer |
oqlgcyl | LocalLLaMA | 1u0xaml | 1u0xaml | 0 | [deleted] | 1,780,988,022 | [deleted] | 0 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqlgcyl/ | 1,789,194,982 | batch-priority-2026-summer |
oqlibvo | LocalLLaMA | 1u0xaml | 1u0xaml | 0 | audioen | 1,780,989,015 | Unsloth stated that Q4_0 can't represent the QAT model accurately, so my expectation that it is because Q4_0 format is not appropriate for Gemma-4 QAT and therefore llama.cpp should not be used with this or any other QAT model from the Gemma family until the issue is fixed.
The key problem is that Q4_0 uses F16 forma... | 22 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqlibvo/ | 1,789,194,982 | batch-priority-2026-summer |
oqlj4w4 | LocalLLaMA | 1u0xaml | oqlfjxh | 1 | audioen | 1,780,989,428 | Yes, it seems so. GGUF Q4_0 format can't represent the original QAT model weights, so it is altered by the process of expressing as Q4_0, and has lost accuracy as consequence. | 3 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqlj4w4/ | 1,789,194,982 | batch-priority-2026-summer |
oqm1k5z | LocalLLaMA | 1u0xaml | oqlibvo | 1 | 413205 | 1,780,999,207 | May I ask for the "unsloth stated" source? | 1 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqm1k5z/ | 1,789,194,982 | batch-priority-2026-summer |
oqm9rqw | LocalLLaMA | 1u0xaml | 1u0xaml | 0 | ABLPHA | 1,781,002,944 | https://unsloth.ai/docs/models/gemma-4/qat#:~:text=We%20found%20that%20naively%20converting%20the%20QAT%20Q4%5F0%20checkpoint%20to%20Q4%5F0%20in%20llama%2Ecpp%20land%20actually%20degraded%20accuracy%20and%20was%20not%20actually%20aligned%20with%20the%20BF16%20QAT%20lattice%20for%20Q4%5F0%2E | 2 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqm9rqw/ | 1,789,194,998 | batch-priority-2026-summer |
oqmh7fv | LocalLLaMA | 1u0xaml | oqlgcyl | 1 | silenceimpaired | 1,781,005,897 | “At no point in your rambling, incoherent response were you even close to anything that could be considered a rational thought. Everyone in this room is now dumber for having listened to it. I award you no points, and may God have mercy on your soul.” | 5 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqmh7fv/ | 1,789,194,982 | batch-priority-2026-summer |
oqmklun | LocalLLaMA | 1u0xaml | oqlibvo | 1 | DunderSunder | 1,781,007,125 | Does vllm version have these problems? Also, was the gemma 3 QAT fine? I don't remember it having issues. | 1 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqmklun/ | 1,789,194,982 | batch-priority-2026-summer |
oqn8y2q | LocalLLaMA | 1u0xaml | oqm9rqw | 1 | 413205 | 1,781,014,628 | thanks | 1 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqn8y2q/ | 1,789,194,990 | batch-priority-2026-summer |
oqynlmc | LocalLLaMA | 1u0xaml | 1u0xaml | 0 | Front-University4363 | 1,781,146,141 | Really interesting — it lines up with what I found measuring Gemma 4 QAT (the 12B): the QAT quality edge is much smaller than the headline, and against a good non-QAT quant it can vanish. A few things that might explain QAT < IQ4_XS for you:
Sample size — 11 vs 14 on ~20 questions is within noise; I'd want more quest... | 1 | null | /r/LocalLLaMA/comments/1u0xaml/comment/oqynlmc/ | 1,789,194,982 | batch-priority-2026-summer |
oqlf266 | LocalLLaMA | 1u0xb2u | 1u0xb2u | 0 | AutoModerator | 1,780,987,380 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | false | /r/LocalLLaMA/comments/1u0xb2u/have_you_ever_faced_this_problem/oqlf266/ | 1,789,194,979 | batch-priority-2026-summer |
oqlfimp | LocalLLaMA | 1u0xdfl | 1u0xdfl | 0 | AutoModerator | 1,780,987,605 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 0 | false | https://www.reddit.com/r/LocalLLaMA/comments/1u0xdfl/what_models_would_you_run_for_agentic_coding_on/oqlfimp/ | 1,789,194,978 | batch-priority-2026-summer |
oqlgx88 | LocalLLaMA | 1u0xhj5 | 1u0xhj5 | 0 | sloth_cowboy | 1,780,988,301 | Asrock x870e Taichi lite. Dual pcie gen 5 x16 slots, and supports bifurcated x8/x8 or x4/x4/x4/x4 if you plan to use MCIO setup. | 5 | null | /r/LocalLLaMA/comments/1u0xhj5/is_there_any_consumergrade_motherboard_with_dual/oqlgx88/ | 1,789,194,981 | batch-priority-2026-summer |
oqlgx8d | LocalLLaMA | 1u0xhj5 | 1u0xhj5 | 0 | FullstackSensei | 1,780,988,301 | Consumer platforms, by their very cost conscious nature, are limited in the number of lanes you get from the CPU. How can a board have two x16 slots when CPUs are limited to ~24 lanes, some of which need to go to NVMe?
Whats your problem with workstation or server platforms? Your use case is literally what they're des... | 3 | null | /r/LocalLLaMA/comments/1u0xhj5/is_there_any_consumergrade_motherboard_with_dual/oqlgx8d/ | 1,789,194,981 | batch-priority-2026-summer |
oqlgxjf | LocalLLaMA | 1u0xhj5 | 1u0xhj5 | 0 | Poha_Best_Breakfast | 1,780,988,306 | Asus proart x870E which I have has 2 x8 slots. I think the MSI godlike, asrock taichi and Asus x870E crosshair hero also do.
To get PCIe 5.0 x8 and x8 you’ll need to have GPUs that do support PCIe 5.0. If the GPU is say an RTX 3090 it’ll fall back to PCIe 4.0 x8 | 15 | null | /r/LocalLLaMA/comments/1u0xhj5/is_there_any_consumergrade_motherboard_with_dual/oqlgxjf/ | 1,789,194,981 | batch-priority-2026-summer |
oqlgyuf | LocalLLaMA | 1u0xhj5 | 1u0xhj5 | 0 | raging_giant | 1,780,988,324 | You can split many PCIe5 x16 into two x8 slots but to go more than a few centimetres and you are in for a world of hurt with retimers. High end desktop is basically dead at this point. You are better off with used enterprise gear if you need more PCIe lanes or 2nd hand threadripper. | 2 | null | /r/LocalLLaMA/comments/1u0xhj5/is_there_any_consumergrade_motherboard_with_dual/oqlgyuf/ | 1,789,194,981 | batch-priority-2026-summer |
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