name string | body string | score int64 | controversiality int64 | created timestamp[us] | author string | collapsed bool | edited timestamp[us] | gilded int64 | id string | locked bool | permalink string | stickied bool | ups int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
t1_o8e2hyf | Video streaming, generally for gaming. Open source implementation of nvidias streaming. | 1 | 0 | 2026-03-03T10:52:41 | ravage382 | false | null | 0 | o8e2hyf | false | /r/LocalLLaMA/comments/1rjh5wg/unsloth_fixed_version_of_qwen3535ba3b_is/o8e2hyf/ | false | 1 |
t1_o8e2d2c | Only 1/4 of it's attention really "looks" at the whole context. 3/4 of its attention looks at "fixed" indexes, It Is not stored in KV cache (so KV Is Really light) and its math Is really Easy to compute | 1 | 0 | 2026-03-03T10:51:30 | Pentium95 | false | null | 0 | o8e2d2c | false | /r/LocalLLaMA/comments/1rjff88/how_do_i_get_the_best_speed_out_of_qwen_35_9b_in/o8e2d2c/ | false | 1 |
t1_o8e29ne | Where’s qwen3 coder next | 1 | 0 | 2026-03-03T10:50:39 | StardockEngineer | false | null | 0 | o8e29ne | false | /r/LocalLLaMA/comments/1rivckt/visualizing_all_qwen_35_vs_qwen_3_benchmarks/o8e29ne/ | false | 1 |
t1_o8e29gf | It’s fine as an introduction to local models. | 1 | 0 | 2026-03-03T10:50:36 | ProfessionalSpend589 | false | null | 0 | o8e29gf | false | /r/LocalLLaMA/comments/1rjb7yk/psa_if_you_want_to_test_new_models_use/o8e29gf/ | false | 1 |
t1_o8e27ov | Heretic doesn't use backprop training, but given the number of epochs you're using at this point for the parameter search how valuable is that still really?
If you use backprop training with the same LORAs and a weighted loss for the refusals (first relevant token, just like now) you can forget about layer weighting, you don't need to worry about MLP vs attention. Set the weight for refusal loss and let backprop handle it all. If a layer/MLP causes too much KL divergence, the LORAs there will simply become pass through.
I'd really like to see a Heretic vs FT face off using the same dataset and LORAs for training time and quality. | 1 | 0 | 2026-03-03T10:50:09 | PinkysBrein | false | null | 0 | o8e27ov | false | /r/LocalLLaMA/comments/1qa0w6c/it_works_abliteration_can_reduce_slop_without/o8e27ov/ | false | 1 |
t1_o8e25ma | Airbus A320-200:
https://preview.redd.it/dnbht8ti8tmg1.jpeg?width=1000&format=pjpg&auto=webp&s=082ce505da094d6e28b7127659dc5fbc72831052
| 1 | 0 | 2026-03-03T10:49:38 | -Ellary- | false | null | 0 | o8e25ma | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8e25ma/ | false | 1 |
t1_o8e1xi8 | Oh I haven't checked it yet. Does the model have some kinda parameters for uncensored purposes? Do I just find out by asking a query? | 1 | 0 | 2026-03-03T10:47:37 | Zealousideal-Check77 | false | null | 0 | o8e1xi8 | false | /r/LocalLLaMA/comments/1rj4nnq/qwen352b_on_android/o8e1xi8/ | false | 1 |
t1_o8e1u4v | Try the other 6 quants and/or the settings for temperature and penalties mentioned on the page of the model. | 1 | 0 | 2026-03-03T10:46:44 | ProfessionalSpend589 | false | null | 0 | o8e1u4v | false | /r/LocalLLaMA/comments/1rjb7yk/psa_if_you_want_to_test_new_models_use/o8e1u4v/ | false | 1 |
t1_o8e1ron | In llama.cpp I would guess it’s the kwargs flag you can set but does that only work in terminal or could it also work in a gui frontend? As you can see in the screenshot, there seems to be a gui button for thinking, unless I’m misinterpreting it and it’s just an indicator, no button. | 1 | 0 | 2026-03-03T10:46:07 | ProdoRock | false | null | 0 | o8e1ron | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8e1ron/ | false | 1 |
t1_o8e1r0q | Ask the ai 🤣 | 1 | 0 | 2026-03-03T10:45:57 | Forsaken_Address8812 | false | null | 0 | o8e1r0q | false | /r/LocalLLaMA/comments/1rianwb/running_qwen35_27b_dense_with_170k_context_at/o8e1r0q/ | false | 1 |
t1_o8e1mm0 | Do you have the dgx connected for distributed inference? Are you doing that size so you can fit other models as well? My strix halo can fit q6 and xcreates made a video showing the quant does affect the output. Just curious why you chose q3 with 2x dgx. I get the same speed at q6kxl i just trust it a bit more. | 1 | 0 | 2026-03-03T10:44:50 | GCoderDCoder | false | null | 0 | o8e1mm0 | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8e1mm0/ | false | 1 |
t1_o8e1mfn | Thats good! I am running a potato pc and pushing for 3t/s now | 1 | 0 | 2026-03-03T10:44:48 | Last-Shake-9874 | false | null | 0 | o8e1mfn | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8e1mfn/ | false | 1 |
t1_o8e1khe | > We should ask what inference stack they are using when people post here asking for Qwen3.5 help
People should learn how to ask simple questions.
| 1 | 0 | 2026-03-03T10:44:18 | ProfessionalSpend589 | false | null | 0 | o8e1khe | false | /r/LocalLLaMA/comments/1rjb7yk/psa_if_you_want_to_test_new_models_use/o8e1khe/ | false | 1 |
t1_o8e1ip0 | My only recommendation is to take care to not end up with this. You need to direct because you are designing for humans.
https://preview.redd.it/otnlwrgc7tmg1.png?width=495&format=png&auto=webp&s=652af366daa902c49acbd6c56e6c650762c50d4d
| 1 | 0 | 2026-03-03T10:43:49 | schnauzergambit | false | null | 0 | o8e1ip0 | false | /r/LocalLLaMA/comments/1rjlru3/extended_godot_mcp_from_20_to_149_tools_aiming/o8e1ip0/ | false | 1 |
t1_o8e1hf4 | using it with vllm cu130 and is working perfect with opencode. had no tool call errors at all. (using official fp8 weights)
until now its the only open weight model i tried (below 200b) which is totally useful and can replace my glm and minimax sub | 1 | 0 | 2026-03-03T10:43:31 | Pitiful_Task_2539 | false | null | 0 | o8e1hf4 | false | /r/LocalLLaMA/comments/1rf4viw/qwen_35_122b_tool_calls_in_opencode/o8e1hf4/ | false | 1 |
t1_o8e1h96 | Last time I checked, Cline still did not support native tool calls on OpenAI-compatible endpoint. Try Roo Code instead, it uses native tool calling by default. If still having issues, double check that you have most recent quants (Unsloth recently recreated their quants, old ones were broken). If quant is good, try using bf16 or f32 cache; f16 cache (the default in llama.cpp) known to cause issues, and quantizing cache even more so. For small models, good idea to use Q6 or Q8. If still having issues, I suggest trying 27B or 35B-A3B, with at least Q5 or higher quant. | 1 | 0 | 2026-03-03T10:43:28 | Lissanro | false | null | 0 | o8e1h96 | false | /r/LocalLLaMA/comments/1rjfijf/cline_not_playing_well_with_the_freshly_dropped/o8e1h96/ | false | 1 |
t1_o8e1flq | I have a secret formula I am currently using and still in the works, The Q4\_K\_M is about 260GB yes. and on humaneval bench I am getting now 2.2 tokens/second | 1 | 0 | 2026-03-03T10:43:04 | Last-Shake-9874 | false | null | 0 | o8e1flq | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8e1flq/ | false | 1 |
t1_o8e1bb6 | Could I run the 35b moe model with 8gb vram and 16 gb ddr5 ram? | 1 | 0 | 2026-03-03T10:41:58 | kedarkhand | false | null | 0 | o8e1bb6 | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8e1bb6/ | false | 1 |
t1_o8e198e | I spent all my money on two DGX Sparks and an RTX Pro 6000, two 5090s and two A6000s. I’m all tapped out.
Well, I guess we’ll never know if your numbers are even valid. Too bad. | 1 | 0 | 2026-03-03T10:41:26 | StardockEngineer | false | null | 0 | o8e198e | false | /r/LocalLLaMA/comments/1rj3i8m/strix_halo_npu_performance_compared_to_gpu_and/o8e198e/ | false | 1 |
t1_o8e196c | O yes that is true, I am pushing the limits to see what is the biggest usable model I can run on consumer hardware throwing in a little pezaz of my own to load these models I am doing optimization still and running it through humaneval to see some results, currently hitting 2.2 t/s now
| 1 | 0 | 2026-03-03T10:41:25 | Last-Shake-9874 | false | null | 0 | o8e196c | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8e196c/ | false | 1 |
t1_o8e0xep | How does it fit into 12GB VRAM and 48GM RAM?
The Q4\_K\_M file is >>60GB
Are you swapping? And you are getting 1.4 t/s!? Thats not bad. Poor SSD - doing lots of work.
Get some additional RAM :-)
I tested modells when their answers ran a full night.
For testing, what is the quality of the model, speed does not matter in my eyes.
| 1 | 0 | 2026-03-03T10:38:23 | Impossible_Art9151 | false | null | 0 | o8e0xep | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8e0xep/ | false | 1 |
t1_o8e0uf8 | Ahh thanks for pointing that out. It definitely got faster but not as fast as cache reuse in my potato hardware, cache reuse was snappy like 1 sec but ne checkpointing is more like 7-10 sec to the first tok. | 1 | 0 | 2026-03-03T10:37:37 | FORNAX_460 | false | null | 0 | o8e0uf8 | false | /r/LocalLLaMA/comments/1ricz8u/notice_qwen_35_reprocessing_the_prompt_every_time/o8e0uf8/ | false | 1 |
t1_o8e0qo3 | Yes! I shouldn't have forgotten that, thanks! | 1 | 0 | 2026-03-03T10:36:37 | CryptographerKlutzy7 | false | null | 0 | o8e0qo3 | false | /r/LocalLLaMA/comments/1rjk9tt/are_all_models_censored_like_this/o8e0qo3/ | false | 1 |
t1_o8e0q5o | Go for qwen 3.5 9b q4 k xl... Gpu offload: 32, context size: start from 20k, I have a 12 gigs gpu and the max it can go without crashing or slowing my PC is 50k, above that it just starts to generate slow t/s. I have this model locally hosted on my whole network and using it from my phone as well just with the addition of a few mcps. Working really good so far. And yesterday I tested it out with a few coding tasks on my actual project on which I am working on, obviously it is not as good as the high end models but it's pretty impressive, and knows what it's doing but keep it limited to 2 or 3 files per query, otherwise it might not be able to handle the context. | 1 | 0 | 2026-03-03T10:36:29 | Zealousideal-Check77 | false | null | 0 | o8e0q5o | false | /r/LocalLLaMA/comments/1rjkarj/local_model_suggestions_for_medium_end_pc_for/o8e0q5o/ | false | 1 |
t1_o8e0pmf | A major update for Agentic Memory is also planned! | 1 | 0 | 2026-03-03T10:36:20 | Active_Concept467 | false | null | 0 | o8e0pmf | false | /r/LocalLLaMA/comments/1r8bc65/built_a_shared_memory_interagent_messaging_layer/o8e0pmf/ | false | 1 |
t1_o8e0ova | Here from the future
Cant tell ya kid
It s storm here,
enjoy while you can | 1 | 0 | 2026-03-03T10:36:09 | single_shot_ | false | null | 0 | o8e0ova | false | /r/LocalLLaMA/comments/1rj5ngc/running_qwen3508b_on_my_7yearold_samsung_s10e/o8e0ova/ | false | 1 |
t1_o8e0o2r | I trained for two days, using an RTX 4060TI GPU. | 1 | 0 | 2026-03-03T10:35:57 | Forsaken_Shopping481 | false | null | 0 | o8e0o2r | false | /r/LocalLLaMA/comments/1rjjvge/update_tinytts_the_smallest_english_tts_model/o8e0o2r/ | false | 1 |
t1_o8e0n7u | comparison of languages and accuracy [https://github.com/openai/whisper/discussions/2363](https://github.com/openai/whisper/discussions/2363) | 1 | 0 | 2026-03-03T10:35:43 | inh24 | false | null | 0 | o8e0n7u | false | /r/LocalLLaMA/comments/1fvb83n/open_ais_new_whisper_turbo_model_runs_54_times/o8e0n7u/ | false | 1 |
t1_o8e0k5l | We are currently preparing to support multiple models including ChatGPT and others. An update is planned for March 8th! | 1 | 0 | 2026-03-03T10:34:54 | Active_Concept467 | false | null | 0 | o8e0k5l | false | /r/LocalLLaMA/comments/1r8bc65/built_a_shared_memory_interagent_messaging_layer/o8e0k5l/ | false | 1 |
t1_o8e0j9y | It was the best of times, it was the blurst of times? | 1 | 0 | 2026-03-03T10:34:40 | ptear | false | null | 0 | o8e0j9y | false | /r/LocalLLaMA/comments/1rizodv/running_qwen_35_08b_locally_in_the_browser_on/o8e0j9y/ | false | 1 |
t1_o8e0f7f | Why is no one acknowledging the fact that the model sees context outside of "hi" and tries to decide how to handle language switch? | 1 | 0 | 2026-03-03T10:33:34 | kaisurniwurer | false | null | 0 | o8e0f7f | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8e0f7f/ | false | 1 |
t1_o8e0dfq | WER comparison [https://github.com/openai/whisper/discussions/2363](https://github.com/openai/whisper/discussions/2363) | 1 | 0 | 2026-03-03T10:33:06 | inh24 | false | null | 0 | o8e0dfq | false | /r/LocalLLaMA/comments/1fvb83n/open_ais_new_whisper_turbo_model_runs_54_times/o8e0dfq/ | false | 1 |
t1_o8e0byk | Great job, now extract a lora and set weight = -1 | 1 | 0 | 2026-03-03T10:32:41 | woct0rdho | false | null | 0 | o8e0byk | false | /r/LocalLLaMA/comments/1rj89qy/merlin_research_released_qwen354bsafetythinking_a/o8e0byk/ | false | 1 |
t1_o8e08ii | That isn’t how this works. If the point in time comes, that Opus 4.6 Level of coding locally is actually available - there will be Opus 5 or 6 in the cloud and you will want that. | 1 | 0 | 2026-03-03T10:31:46 | Danmoreng | false | null | 0 | o8e08ii | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8e08ii/ | false | 1 |
t1_o8e077t | Thank you for the UX compliment.
I think largely where I'm coming form is, if you've got openclaw already does it even make sense to have an ondevice personal assistant? The results will never be comparable, but data will remain on device.
IDK if thats a large enough moat, and I haven't been able to feel enough pull from the community. Typically people want RAG, and agentic AI, but haven't felt pull for a personal assistant. But I feel like I solving something bigger than RAG and agentic AI locally.
| 1 | 0 | 2026-03-03T10:31:25 | alichherawalla | false | null | 0 | o8e077t | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8e077t/ | false | 1 |
t1_o8e03ba | I used openrouter for approx. 4 months. The main benefits were the cost control feature and possibility to route to different models. I used it in a semi-prod setup (internal tools + a small customer-facing feature). It was nice for fast experiments, but at scale some things pushed me off. The main ones are sudden latency spikes (the average latency was ok, but P95/P99 would randomly spike depending on which provider the request got routed to - from 2-3 secs to 15-20 secs) and opaque debugging.
I've moved to llm api ai. It has much better speed stability and clear monitoring features for credit usage per feature/user/provider and debugging alike. Also this platform was way more stable, haven't experienced any downtime whatsoever. | 1 | 0 | 2026-03-03T10:30:24 | Angelic_Insect_0 | false | null | 0 | o8e03ba | false | /r/LocalLLaMA/comments/1p2fnm8/anyone_here_using_openrouter_what_made_you_pick_it/o8e03ba/ | false | 1 |
t1_o8e02id | 1. There was no M4 ultra :)
2. I'll gladly await a further support of QLoRA for QWEN 3.5 MoEs | 1 | 0 | 2026-03-03T10:30:11 | Desperate-Sir-5088 | false | null | 0 | o8e02id | false | /r/LocalLLaMA/comments/1rj7y9d/pmetal_llm_finetuning_framework_for_apple_silicon/o8e02id/ | false | 1 |
t1_o8e00xu | Sorry, but you’re wrong about the Qwen models.
You are right about Ollama and other hosting frameworks, but as good as the Qwen models are, they have a serious issues which no one, including Qwen, is addressing.
A significant part of their benchmark improvement comes from inference time reasoning. Turn it off, and the scores drop notably. That’s not a problem in itself. What *is* a problem is twofold:
1) If you read the original Qwen model descriptions, towards the end of a very long document in “considerations” they casually mention that for the 27B/35B the *minimum* safe context for daily use is 32K!!! For **any** query. Below that, there’s a chance the model will stop responding early because it doesn’t have enough context to reason in. It gets worse. If you have an unusually hard problem that genuinely requires extended thinking, the *minimum* suggested context is 80K!!! Just to accommodate the reasoning.
2) As if the minimum context wasn’t bad enough, the model has been so overtrained on thinking that it bleeds through when thinking is disabled, so there’s no way to permanently turn it off. You may not have thinking tags with it turned off, but your prompt includes a suggestion of thinking or reasoning then the model regularly outputs 30-80k of thinking steps.
Don’t get me wrong, the outputs and benchmark scores are genuinely impressive, but it’s completely unusable as a daily driver unless you don’t mind 10-20 minute long pauses while it reasons and you have enough VRAM to accommodate the huge minimum context requirements.
Qwen 3.5 does exactly what Anthropic did with their latest 4.6 models - they exploited a known loophole in current the benchmarking process which scores models without accounting for either speed of response or tokens used to achieve the score. Both of which matter in the real world, especially if you’re paying for tokens. | 1 | 0 | 2026-03-03T10:29:46 | StuartGray | false | null | 0 | o8e00xu | false | /r/LocalLLaMA/comments/1rjb7yk/psa_if_you_want_to_test_new_models_use/o8e00xu/ | false | 1 |
t1_o8dztyf | accuracy comparison [https://github.com/openai/whisper/discussions/2363](https://github.com/openai/whisper/discussions/2363) | 1 | 0 | 2026-03-03T10:27:54 | inh24 | false | null | 0 | o8dztyf | false | /r/LocalLLaMA/comments/1fvb83n/open_ais_new_whisper_turbo_model_runs_54_times/o8dztyf/ | false | 1 |
t1_o8dzs7p | You asked if I’m using OpenClaw locally on my phone:
not directly, I run OpenClaw on my laptop and control it from my phone via Telegram, with remote access secured through Tailscale.
Right now, I also expose an OpenAI-compatible endpoint from MNN Chat when I need a local provider (the app has an OAI-compatible API), allowing OpenClaw and other clients to communicate with it.
I just discovered your Android app, and it’s the best UX I’ve seen for on-device LLMs, my only wish is to use it as a full replacement for MNN Chat, especially if you add an OpenAI-compatible server/API mode.
Regarding the use case for exposing it as a server:
yes, keeping it local but accessible on LAN or your tailnet is useful as a second provider/sub-agent for fast tasks (doc/image extraction, quick summaries, lightweight vision), while OpenClaw manages routing, memory, and channels.
For adoption:
your “mobile-first personal assistant that runs local models” approach makes sense, what will retain users are 2, 3 killer workflows (e.g., “send a screenshot/doc → get structured notes + action items,” “receipt/invoice → fields into a template,” “image → OCR + short summary”), plus safe integrations (calendar is usually straightforward; WhatsApp automation can be tricky due to platform rules, so I’d start read-only/notification-first). Also Telegram over WhatsApp. | 1 | 0 | 2026-03-03T10:27:26 | RIP26770 | false | null | 0 | o8dzs7p | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8dzs7p/ | false | 1 |
t1_o8dzqft | You must have a really old smartphone. :)
Currently even for 280 USD smartphones have 12 GB of ram | 1 | 0 | 2026-03-03T10:26:58 | Healthy-Nebula-3603 | false | null | 0 | o8dzqft | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dzqft/ | false | 1 |
t1_o8dzqb8 | Ok... try now, I have uploaded a higher resolution version | 1 | 0 | 2026-03-03T10:26:57 | CapitalShake3085 | false | null | 0 | o8dzqb8 | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8dzqb8/ | false | 1 |
t1_o8dzkwq | Nice! How long did it take you to train, and which GPU? | 1 | 0 | 2026-03-03T10:25:31 | Direct-Argument-7066 | false | null | 0 | o8dzkwq | false | /r/LocalLLaMA/comments/1rjjvge/update_tinytts_the_smallest_english_tts_model/o8dzkwq/ | false | 1 |
t1_o8dzekv | Loved this tool bro! | 1 | 0 | 2026-03-03T10:23:52 | No-Marketing-2294 | false | null | 0 | o8dzekv | false | /r/LocalLLaMA/comments/1nay7wk/need_a_free_simple_tool_of_whisperv3turbo/o8dzekv/ | false | 1 |
t1_o8dzd3p | [deleted] | 1 | 0 | 2026-03-03T10:23:28 | [deleted] | true | null | 0 | o8dzd3p | false | /r/LocalLLaMA/comments/1r2ptd5/using_glm5_for_everything/o8dzd3p/ | false | 1 |
t1_o8dzcsi | good catch PRed: [https://github.com/mungg/OneRuler/pull/2](https://github.com/mungg/OneRuler/pull/2) | 1 | 0 | 2026-03-03T10:23:24 | uhuge | false | null | 0 | o8dzcsi | false | /r/LocalLLaMA/comments/1omst7q/polish_is_the_most_effective_language_for/o8dzcsi/ | false | 1 |
t1_o8dz94g | Yes, but the local large models are not very intelligent. I have used Qwen3:8b and Qwen3.5:9b. Some minor functions cannot be achieved, and they are not as good as the online models. I suggest using the online models first. | 1 | 0 | 2026-03-03T10:22:26 | CollectionKey2320 | false | null | 0 | o8dz94g | false | /r/LocalLLaMA/comments/1qv6892/help_setting_local_ollama_models_with_openclaw/o8dz94g/ | false | 1 |
t1_o8dz6xh | Also claiming that a q4 quant of the very latest model of whatever number of prams drop should by nature be entirely unuseable is a _wild_ take | 1 | 0 | 2026-03-03T10:21:51 | Competitive_Ad_5515 | false | null | 0 | o8dz6xh | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dz6xh/ | false | 1 |
t1_o8dz4ym | Sorry, I forgot to mention the quant in hurry. Updated my comment. | 1 | 0 | 2026-03-03T10:21:22 | pmttyji | false | null | 0 | o8dz4ym | false | /r/LocalLLaMA/comments/1rji5bc/how_do_the_small_qwen35_models_compare_to_the/o8dz4ym/ | false | 1 |
t1_o8dz1bo | Yeah, because only q4_0 and q8_0 run nicely and natively accelerated on my NPU? There's some great work being done with them for sure, but dynamically weighted quants don't run well on my mobile device.
I also ran quants of the 4B and got similar, my phone usually handles up to 8B models ok.
It's probably a config issue on my end, but I'm sharing my bad first impression of the 3.5 model drop. I'm sure they'll be great once I get settings dialed in and I find the right quant for my use-cases. And for the record I love qwen, 2.5 was my jam. | 1 | 0 | 2026-03-03T10:20:24 | Competitive_Ad_5515 | false | null | 0 | o8dz1bo | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dz1bo/ | false | 1 |
t1_o8dyvys | I think you need a classifier as your filter, then pass it to a more capable model, no need of using VLM on a task that more reliable traditional methods works. | 1 | 0 | 2026-03-03T10:18:57 | Chemical_Owl_6352 | false | null | 0 | o8dyvys | false | /r/LocalLLaMA/comments/1rjkyq9/fast_free_vlm_for_object_id_quality_filtering/o8dyvys/ | false | 1 |
t1_o8dyt54 | make sure resizable bar and above 4g decoding are on, and maybe check if your 3090 firmware has the resizable bar update, you could also try a regular ol' bios/uefi update | 1 | 0 | 2026-03-03T10:18:12 | llama-impersonator | false | null | 0 | o8dyt54 | false | /r/LocalLLaMA/comments/1rjdeat/dual_rtx_3090_on_b550_70b_models_produce_garbage/o8dyt54/ | false | 1 |
t1_o8dyrxo | No? I already told you i didn't read the post's body so i just assumed it was only about saying "hi"
Also i can't read your image it's too pixelated | 1 | 0 | 2026-03-03T10:17:52 | Velocita84 | false | null | 0 | o8dyrxo | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8dyrxo/ | false | 1 |
t1_o8dyofb | This is a bit reductive and there are plenty of edge cases, but in general:
* Llama.cpp/ik_llama.cpp for CPU or CPU/GPU hybrid inference.
* VLLM for multi-GPU inference.
Just a general guideline, there are certainly scenarios that fall outside of this. | 1 | 0 | 2026-03-03T10:16:55 | RG_Fusion | false | null | 0 | o8dyofb | false | /r/LocalLLaMA/comments/1rjk2dq/im_a_noob_to_local_inference_how_do_you_choose/o8dyofb/ | false | 1 |
t1_o8dykpv | Hey, could you please answer some noob questions, please?
1. What settings are recommended? I'm planning to use this model in a chat bot without thinking.
2. Is this model capable of using tools without thinking? Or do I need to explicitly say in the prompt "use X tool"? | 1 | 0 | 2026-03-03T10:15:54 | groosha | false | null | 0 | o8dykpv | false | /r/LocalLLaMA/comments/1rjlaxj/finished_a_qwen_35_9b_opus_45_distill/o8dykpv/ | false | 1 |
t1_o8dyh9o | Not for the home, unless you have a number of gpu's.
MoE's are fast with a batch of 1. But they can slow down when you get more in flight since the different token sequences being run in parallel will activate different experts. So memory bandwidth takes a hit. One way to get around that is to deploy multiple copies of the models such that different experts gets their own bandwidth so to speak.
Dense models don't have this issue and the speed can be increased with speculative decoding. | 1 | 0 | 2026-03-03T10:14:58 | RnRau | false | null | 0 | o8dyh9o | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8dyh9o/ | false | 1 |
t1_o8dygmw | Sem comparativos? | 1 | 0 | 2026-03-03T10:14:49 | charmander_cha | false | null | 0 | o8dygmw | false | /r/LocalLLaMA/comments/1rjlaxj/finished_a_qwen_35_9b_opus_45_distill/o8dygmw/ | false | 1 |
t1_o8dyfgk | Anyone fancy explaining what this is? | 1 | 0 | 2026-03-03T10:14:30 | Melodic_Reality_646 | false | null | 0 | o8dyfgk | false | /r/LocalLLaMA/comments/1rjhmmf/presence_penalty_seems_to_be_incoming_on_lmstudio/o8dyfgk/ | false | 1 |
t1_o8dyfe5 | Haha massive model for your machine. MASSIVE | 1 | 0 | 2026-03-03T10:14:29 | nakedspirax | false | null | 0 | o8dyfe5 | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8dyfe5/ | false | 1 |
t1_o8dydif | Can or work with Antigravity Gemini/Claude models ? | 1 | 0 | 2026-03-03T10:13:59 | Dapper-Neat9261 | false | null | 0 | o8dydif | false | /r/LocalLLaMA/comments/1r8bc65/built_a_shared_memory_interagent_messaging_layer/o8dydif/ | false | 1 |
t1_o8dyas0 | Just download Heretic versions. | 1 | 0 | 2026-03-03T10:13:14 | -Ellary- | false | null | 0 | o8dyas0 | false | /r/LocalLLaMA/comments/1regq10/qwen_35_2735122b_jinja_template_modification/o8dyas0/ | false | 1 |
t1_o8dy84q | I'm assuming that is your unloaded speed before adding any context. It probably drops below 1 t/s after a bit of use, but you could answer that better than I can.
If you're purchasing a computer explicitly for running large models, you're much better off getting a Mac Pro or an EPYC server. I went the server route, and get 16 tokens/second on Q5-K-XL. I understand that not everyone has the opportunity to build out a system like this, so what you're doing is a legitimate alternative.
Still, I have to ask, what can someone do with a 1 token/second model? | 1 | 0 | 2026-03-03T10:12:31 | RG_Fusion | false | null | 0 | o8dy84q | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8dy84q/ | false | 1 |
t1_o8dy04s | 800m param btw. Incredible work Qwen !
Large (small) language models | 1 | 0 | 2026-03-03T10:10:25 | getpodapp | false | null | 0 | o8dy04s | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8dy04s/ | false | 1 |
t1_o8dxzad | finally some good content on this sub | 1 | 0 | 2026-03-03T10:10:11 | pythonlover001 | false | null | 0 | o8dxzad | false | /r/LocalLLaMA/comments/1rhx5pc/reverse_engineered_apple_neural_engineane_to/o8dxzad/ | false | 1 |
t1_o8dxyr6 | Pretty sure IQ4\_NL is as fast but also way smarter. And weren't Q\_K quants finally optimized for ARM a few months ago? | 1 | 0 | 2026-03-03T10:10:03 | ABLPHA | false | null | 0 | o8dxyr6 | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dxyr6/ | false | 1 |
t1_o8dxv01 | Unsloth dynamic quant v2 q5 or q6 will be quick good good quality | 1 | 0 | 2026-03-03T10:09:04 | getpodapp | false | null | 0 | o8dxv01 | false | /r/LocalLLaMA/comments/1rjff88/how_do_i_get_the_best_speed_out_of_qwen_35_9b_in/o8dxv01/ | false | 1 |
t1_o8dxutv | Swizzling is replacing by reference. It was a silly joke since saying “sorry can’t answer your exact question but” sounded bot like, yet you’ve been outspoken about bots and slop and such | 1 | 0 | 2026-03-03T10:09:01 | Accomplished_Ad9530 | false | null | 0 | o8dxutv | false | /r/LocalLLaMA/comments/1rjikwz/help_me_create_my_llm_ecosystem/o8dxutv/ | false | 1 |
t1_o8dxqm4 | Interesting. Any hints like that for a desktop pc setup with i7 6700, 24gb ram & gtx1070 with 8gb vram? | 1 | 0 | 2026-03-03T10:07:53 | sydulysses | false | null | 0 | o8dxqm4 | false | /r/LocalLLaMA/comments/1rjkarj/local_model_suggestions_for_medium_end_pc_for/o8dxqm4/ | false | 1 |
t1_o8dxpms | You please go and learn socialist theory first. China is in the preliminary stage of the construction of socialism. They have the market and private enterprise in some fields, but the commanding heights of the economy are fully socially owned and planned. The vast majority of the Chinese economy remains socially owned and directed for the common good by the five year plans, especially the critical sectors like steel, energy, etc. | 1 | 0 | 2026-03-03T10:07:38 | Imperator_Basileus | false | null | 0 | o8dxpms | false | /r/LocalLLaMA/comments/1rd1lmz/american_vs_chinese_ai_is_a_false_narrative/o8dxpms/ | false | 1 |
t1_o8dxphc | Tried the chat online and it confidently gaslighted me many times. This is absolutely not anything usable at least for image input | 1 | 0 | 2026-03-03T10:07:35 | MastodonParty9065 | false | null | 0 | o8dxphc | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dxphc/ | false | 1 |
t1_o8dxjct | HOW!!!, im struggling with 12gb Vram + 64gb Ram to run 27b q4\_k\_m with 32k context. Its 5t/s slow and keeps getting slower over time | 1 | 0 | 2026-03-03T10:05:58 | Beautiful_Egg6188 | false | null | 0 | o8dxjct | false | /r/LocalLLaMA/comments/1rbkeea/which_one_are_you_waiting_for_more_9b_or_35b/o8dxjct/ | false | 1 |
t1_o8dxi2z | No, the KV cache does not grow 100x.
The attention matrix is. | 1 | 0 | 2026-03-03T10:05:37 | Budget_Author_828 | false | null | 0 | o8dxi2z | false | /r/LocalLLaMA/comments/1rj6m71/qwen_35_27b_a_testament_to_the_transformer/o8dxi2z/ | false | 1 |
t1_o8dxg78 | I got the q3kxl unsloth version running on my 2x dgx spark cluster and getting 11t/s | 1 | 0 | 2026-03-03T10:05:07 | CATLLM | false | null | 0 | o8dxg78 | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8dxg78/ | false | 1 |
t1_o8dx9at | Frankly, after using it, it blew me away instantly. I kept using it despite issues with prompt reprocessing. | 1 | 0 | 2026-03-03T10:03:20 | kaisurniwurer | false | null | 0 | o8dx9at | false | /r/LocalLLaMA/comments/1rivckt/visualizing_all_qwen_35_vs_qwen_3_benchmarks/o8dx9at/ | false | 1 |
t1_o8dx3t8 | 4B is on the same level (or higher) as 80B A3B.
Though 4B was always better than it should have been. | 1 | 0 | 2026-03-03T10:01:52 | kaisurniwurer | false | null | 0 | o8dx3t8 | false | /r/LocalLLaMA/comments/1rivckt/visualizing_all_qwen_35_vs_qwen_3_benchmarks/o8dx3t8/ | false | 1 |
t1_o8dx2ib | I can run both but I often prefer the 122b because I can run it way faster. It's semi usable for real work. I recommend you use an unsloth quant. Q3_K_XL is my goto. | 1 | 0 | 2026-03-03T10:01:31 | tylerhardin | false | null | 0 | o8dx2ib | false | /r/LocalLLaMA/comments/1rjldjb/question_on_running_qwen35_397b_q4_k_m/o8dx2ib/ | false | 1 |
t1_o8dx28d | As if that isn't much | 1 | 0 | 2026-03-03T10:01:27 | KaroYadgar | false | null | 0 | o8dx28d | false | /r/LocalLLaMA/comments/1rjd4pv/qwen_25_3_35_smallest_models_incredible/o8dx28d/ | false | 1 |
t1_o8dwyao | Look here: [https://whatmodelscanirun.com/](https://whatmodelscanirun.com/) | 1 | 0 | 2026-03-03T10:00:25 | Chess_pensioner | false | null | 0 | o8dwyao | false | /r/LocalLLaMA/comments/1rifxfe/whats_the_best_local_model_i_can_run_with_16_gb/o8dwyao/ | false | 1 |
t1_o8dwxhk | can you show the code implementation of the tools?
| 1 | 0 | 2026-03-03T10:00:12 | pppp1234543 | false | null | 0 | o8dwxhk | false | /r/LocalLLaMA/comments/1rjh5wg/unsloth_fixed_version_of_qwen3535ba3b_is/o8dwxhk/ | false | 1 |
t1_o8dwooz | Yeah this is the real answer.
Old server parts. ECC DDR4 was somewhat cheap not that long ago. My dual xeon 400GB DDR4 server cost me ~1000USD, which is still not exactly cheap, but for a hobby and with secondary utility of serving as storage server, I didn't mind paying that for a pretty cool hobby.
Though I still mostly use 3090 and smaller models, since prompt processing is quite important for agentic use. | 1 | 0 | 2026-03-03T09:57:54 | kaisurniwurer | false | null | 0 | o8dwooz | false | /r/LocalLLaMA/comments/1rjjcyk/still_a_noob_is_anyone_actually_running_the/o8dwooz/ | false | 1 |
t1_o8dwn2a | I'll look into it | 1 | 0 | 2026-03-03T09:57:28 | Ilishka2003 | false | null | 0 | o8dwn2a | false | /r/LocalLLaMA/comments/1rjdo1i/ollama_keeps_loading_with_openclaw/o8dwn2a/ | false | 1 |
t1_o8dwmaf | yeah that makes sense. Are you using open claw locally on your mobile phone btw? I'm itching to create a mobile first personal assistant that runs local models and now with the qwen3.5 0.8 I feel like it makes sense to do it. Only cause the model is small and intelligent.
But i really don't know about adoption. I'm thinking of very secretary type use cases.
Check whatsapp, and ensure that there are appropriate calendar notifications for all personal obligations so that professional and personal dont' clash.
What are your thoughts? | 1 | 0 | 2026-03-03T09:57:15 | alichherawalla | false | null | 0 | o8dwmaf | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8dwmaf/ | false | 1 |
t1_o8dwjoe | Earlier today?
[https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF/tree/main](https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF/tree/main)
None of the files have been updated today. | 1 | 0 | 2026-03-03T09:56:33 | dark-light92 | false | null | 0 | o8dwjoe | false | /r/LocalLLaMA/comments/1rjhy83/tool_calling_issues_with_qwen3535b_with_16gb_vram/o8dwjoe/ | false | 1 |
t1_o8dwbjc | Yes, it's always great to have a sub-agent that can be added locally to your OpenClaw, for example, for simpler tasks. | 1 | 0 | 2026-03-03T09:54:25 | RIP26770 | false | null | 0 | o8dwbjc | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8dwbjc/ | false | 1 |
t1_o8dwb4w | oh yeah Off Grid allows you to do that + image gen too. Further also allows you to import models if you've got em locally :) | 1 | 0 | 2026-03-03T09:54:18 | alichherawalla | false | null | 0 | o8dwb4w | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8dwb4w/ | false | 1 |
t1_o8dwa01 | 1 | 0 | 2026-03-03T09:54:00 | dummyTukTuk | false | null | 0 | o8dwa01 | false | /r/LocalLLaMA/comments/1rjfyqf/qwen_35_9b_on_a_dual_reasoning_math_game/o8dwa01/ | false | 1 | |
t1_o8dw5nx | thanks! I don't expose it as a server just yet. Is there a use case for it? | 1 | 0 | 2026-03-03T09:52:50 | alichherawalla | false | null | 0 | o8dw5nx | false | /r/LocalLLaMA/comments/1rjec8a/qwen35_on_a_mid_tier_300_android_phone/o8dw5nx/ | false | 1 |
t1_o8dw4s7 | > just two $10k mac ultras [..] You can hook 4 up for $40k
> Hell, for $60k
Yeah, easy.
> it isn't quite as high as you're saying it is.
It is. Even not the 200k (for full GPUs I assume) This is almost starting to touch lower bracket of property values around my parts. | 1 | 0 | 2026-03-03T09:52:36 | kaisurniwurer | false | null | 0 | o8dw4s7 | false | /r/LocalLLaMA/comments/1rjjcyk/still_a_noob_is_anyone_actually_running_the/o8dw4s7/ | false | 1 |
t1_o8dw3vk | 1 | 0 | 2026-03-03T09:52:21 | CapitalShake3085 | false | null | 0 | o8dw3vk | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8dw3vk/ | false | 1 | |
t1_o8dw25s | You're right, however you're missing another aspect - the integrated memory controller (IMC).
With a higher end CPU you're more likely to get a better IMC, which in turn means it can handle higher memory speeds. | 1 | 0 | 2026-03-03T09:51:54 | legit_split_ | false | null | 0 | o8dw25s | false | /r/LocalLLaMA/comments/1ritcfr/imrpove_qwen35_performance_on_weak_gpu/o8dw25s/ | false | 1 |
t1_o8dw1u4 | You should replace ctx-size with fit-ctx and watch the magic happen. | 1 | 0 | 2026-03-03T09:51:49 | Xantrk | false | null | 0 | o8dw1u4 | false | /r/LocalLLaMA/comments/1rjff88/how_do_i_get_the_best_speed_out_of_qwen_35_9b_in/o8dw1u4/ | false | 1 |
t1_o8dvzft | stop using ollama and try llama.cpp like you said | 1 | 0 | 2026-03-03T09:51:11 | jwpbe | false | null | 0 | o8dvzft | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dvzft/ | false | 1 |
t1_o8dvnwk | I'm trying the qwen3.5-4b-mlx in LM Studio, and it says "Wait, one more check." over and over and over. Am I doing something wrong? | 1 | 0 | 2026-03-03T09:48:05 | firesalamander | false | null | 0 | o8dvnwk | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8dvnwk/ | false | 1 |
t1_o8dvnxm | Well you can if you have any recent phone. It's 4 GBs in size with a Q4 Quant and runs pretty well on my phone.
The bigger issue is the speed. I am getting 5 Tok/s on a Oppo Find x9 pro, a flagship phone that's a few months old.
If we get MTP finally working in llama.cpp I can see a near future where this easily reaching the speed of simply reading, which then means it's enough for asking simple questions. | 1 | 0 | 2026-03-03T09:48:05 | OrkanFlorian | false | null | 0 | o8dvnxm | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dvnxm/ | false | 1 |
t1_o8dvmuj | Exactly, I tried it and it confidentially gave a wrong answer and was caught in an infinite thinking loop when I corrected completely wasting battery. | 1 | 0 | 2026-03-03T09:47:48 | ptear | false | null | 0 | o8dvmuj | false | /r/LocalLLaMA/comments/1rjcqm5/qwen_35_4b_is_scary_smart/o8dvmuj/ | false | 1 |
t1_o8dvm16 | Didn't try. | 1 | 0 | 2026-03-03T09:47:34 | MarketingGui | false | null | 0 | o8dvm16 | false | /r/LocalLLaMA/comments/1ritcfr/imrpove_qwen35_performance_on_weak_gpu/o8dvm16/ | false | 1 |
t1_o8dvjt4 | What GPU do you have? | 1 | 0 | 2026-03-03T09:46:59 | tappyson | false | null | 0 | o8dvjt4 | false | /r/LocalLLaMA/comments/1rjh5wg/unsloth_fixed_version_of_qwen3535ba3b_is/o8dvjt4/ | false | 1 |
t1_o8dvg5l | the person creating these benchmarks posts on here once in a while, they have done both https://www.apex-testing.org/ but i'm not 100% confident in the testing method/reliability, esp. considering bad quants on release. but that being said, they have tested both there and the scores look somewhat reasonable | 1 | 0 | 2026-03-03T09:45:59 | fuckingredditman | false | null | 0 | o8dvg5l | false | /r/LocalLLaMA/comments/1riwy9w/is_qwen359b_enough_for_agentic_coding/o8dvg5l/ | false | 1 |
t1_o8dvg7b | What parameters did you find work best if you want to share? | 1 | 0 | 2026-03-03T09:45:59 | DD3Boh | false | null | 0 | o8dvg7b | false | /r/LocalLLaMA/comments/1rj8x1q/qwen35_4b_overthinking_to_say_hello/o8dvg7b/ | false | 1 |
t1_o8dvg2y | Upvote for the software setup (I’ll have to try it someday), but why not just run a SSH daemon and connect with VPN? | 1 | 0 | 2026-03-03T09:45:57 | ProfessionalSpend589 | false | null | 0 | o8dvg2y | false | /r/LocalLLaMA/comments/1rjh5wg/unsloth_fixed_version_of_qwen3535ba3b_is/o8dvg2y/ | false | 1 |
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