r/LocalLLaMA · past month

Qwen 3.6 — October 2026

Community sentiment from 10 posts · 375 comments · collected November 10, 2026 · generated November 10, 2026

Qwen 3.6 — October 2026 scores 60.7/100 overall in the r/LocalLLaMA community benchmark, collected November 10, 2026 from 10 posts and 375 comments. Its strongest category is Speed at 78/100, and its weakest is Creativity & writing at 40/100.

60.7/ 100

Confidence: medium — 10 posts / 375 comments from r/localllama (2026-10, truncated=false), but only 36 comments discuss Qwen 3.6 directly; the strongest signal comes from the dedicated 'Qwen 3.6 35B appreciation post' thread plus the Strata and Snapdragon mini-PC benchmark threads. multimodal_vision has no direct data (null). Sentiment is consistent across threads, with clear pro (speed, agentic use, value) and con (mistakes, coding ceiling, tool-call params) camps.

Category scores

Intelligence

62

Users call it 'smarter than anything else in its class' (milkipedia) and value its broad knowledge: '35B tends to reach for search tools a lot less because it knows more' (PrimeDirective8); '3.8 27b sacrificed general knowledge and reasoning efficiency for coding capability' while 3.6 35b keeps it (Mrinohk, OP of the appreciation post), who adds 'for the speeds it can hit I haven't found a smarter model that is just as fast'. Noted: 'it knows stuff from the beginning of 2026' (PrimeDirective8). Negative: 'it makes so many mistakes all the time' (Naiw80); one user gauges Qwen 3.6/8 27B at '70-80%' of cloud models with thinking off (GrungeWerX).

Coding quality

50

Clearly split. Positive: 'Qwen3.6 35B can code small scripts just fine, and even larger C# projects if you watch over it' (PrimeDirective8); 'made the vanilla quite useful for small coding tasks' after switching to Apex quants (Ueberlord); 'For agentic coding: yes' (Pentium95); 'I had qwen download it and start fixing bugs and adding features I wanted' (buckwheaton); fine-tunes derived from it (Ornith, Tiel) 'have been doing a decent job for coding' (Sensitive_Song4219). Negative: '3.6 35B was never good enough at real coding tasks anyway' (Daniel_H212); 'it makes so many mistakes all the time' (Naiw80); '3.6 35b is bad at long horizon development' (Mrinohk). Consensus: solid for small scripts, weak for real/serious coding.

Instruction following

58

Thin but mostly positive data. The appreciation-post OP lists 'goal following' as a core strength ('Knowledge, reasonably functional coding ability for small scripts, goal following', Mrinohk); 'bigger models making plan, Q36-35 executing, saves a lot of token and time' (feelspeaceman); on a 20+ hour task 'the models don't go insane at all' (Combinatorilliance). milkipedia says he cares 'about tool use and multi-step instruction following' and keeps the model. Negative: repetitive identical pagination offsets in paginated tool calls indicate loop-like misbehavior (Naiw80).

Long context

66

Strong capability data: '50tks on 262k context' on a 12GB 3060 (Miserable-School-665); '120tk/s on a 4070ti ... @ 64k context' and '131tk/s decode, 1859tk/s prefill @ 100k' (oxygen_addiction); '35b was perfectly usable still' at ~100-110k context on a 35W Snapdragon box (WorldlyAd7946); 'starts out at around 2K pre-fill/105 tg, dropping as ctx grows so not too bad' on an Intel B70 (PrimeDirective8). Long-horizon quality is disputed: 'I wouldn't call 3.6 35b bad at long horizon development' (mister2d) vs '3.6 35b is bad at long horizon development' (Mrinohk).

Price / value

70

Recurring value theme: free open-weights MoE running fast on cheap hardware - 8GB 2060 Super (50 tok/s, 60k ctx, ChrizzAUT), 12GB 3060, P100s ('32GB of VRAM for less than $180', Mrinohk), Intel B70, and £300/35W Snapdragon mini PCs ('Two budget PCs able to run a near frontier model locally', killerstreak976). Direct value statements: '35b-a3b is old but for a sub agent or general purpose that old is gold' (notalentwasted); 'saves a lot of token and time' (feelspeaceman); 'available full-quant online for pennies' (EvolvingDior).

Speed

78

The most consistently praised trait. 'For general agent stuff and speed nothing compares' (DistanceAlert5706); 'It's so fast, it can run circles around almost anything else locally' (milkipedia); 'Yes. It's fast to run' (sammybeta); 'while 35b of course is a lot faster' (Naiw80). Measured: '120tk/s on a 4070ti' (oxygen_addiction); '213.3 read / 38.9 write / MTP 55.2' all at 35W (WorldlyAd7946); 'almost 2000 t/s pp and 110 t/s tg' on a B70 (EvolvingDior); '>100 t/s generation' on P100s (Mrinohk). Only negative: the 27B dense version is 'quite slow' vs the sparse 35B MoE on mixed GPU/CPU hardware (Nixellion).

Reliability & uptime

55

Mixed. Positive: 'This model has been my research agent beast for a few months now' (milkipedia - months of continuous use); 'I have q36-35g as a fallback model for a couple of my agents ... they were doing great' (EvolvingDior); '35B shows no sign of badness in my experience' (mister2d). Negative: 'it makes so many mistakes all the time' (Naiw80); the OP reports 'a few issues even at Q8 context that I wasn't having before' in his own setup (Mrinohk, quantization-related).

Creativity & writing

40

Only comparative, unfavorable data in the sample: 'I prefer Gemma 4 26B for its language skills' and 'And yes, for chatting and writing, Gemma 4 wins hands down' (both PrimeDirective8, comparing against Qwen3.6 35B). No user in these files praises the model's creative writing; the 10-16GB VRAM ranking thread notes 'Qwen 27B doesnt really specialize in' roleplay (tableball35, model version ambiguous there).

Multimodal & vision

no data

No data in the sample — the only vision-related post (MiniCPM-V 4.7) credits 'Qwen3.6 for providing the language backbone' with the vision module coming from SigLIP2; no user makes a direct statement about Qwen 3.6's own vision/multimodal capability.

Agentic & tool use

72

Strongly positive: 'This model has been my research agent beast for a few months now' (milkipedia); 'Qwen uses way more tool calls than the Gemma model' (milkipedia); 'For agentic coding: yes' (Pentium95); 'Worse at coding, better at agentic stuff' (Daniel_H212); used as agent fallback where agents 'perform like subagents -- junior devs' and 'were doing great' (EvolvingDior); 'for a sub agent or general purpose that old is gold' (notalentwasted); '35B tends to reach for search tools a lot less because it knows more' (PrimeDirective8). Negative: 'completely hopeless with parameters to the tool call ... 5 calls with the exact same pagination offset' (Naiw80), though completing 'the full toolcall template' is 'reliable'.

Summary

This sample covers the 10 highest-scoring r/localllama posts of 2026-10 that reference Qwen 3.6 (375 comments total), of which 36 discuss the model directly. It appears in two forms: the 35B-A3B MoE, treated as the workhorse for local agents and fast inference, and the 27B dense version, the subject of a '10 things you can do' guide post. The dedicated 'Qwen 3.6 35B appreciation post' and the Strata/Snapdragon benchmark threads carry most of the signal.

The standout strength is speed: users report 120-131 t/s decode at 64k-100k context on a 4070 Ti, 50 t/s at 262k context on a 12GB 3060, ~2000 t/s prefill on an Intel B70, and 213 read / 38.9 write tok/s on a 35W Snapdragon mini PC. Paired with free open weights and low hardware costs (8GB GPUs, P100s, £300 boxes), users frame it as the best intelligence-per-speed and value pick in its class for agentic and general-assistant work: 'for general agent stuff and speed nothing compares', 'my research agent beast for a few months now'.

The weaknesses are quality-side: 'it makes so many mistakes all the time' (one experienced user concluded the 35B is not worth it if you can run the 27B); '3.6 35B was never good enough at real coding tasks anyway' even though small scripts are fine; tool-call parameter handling is called 'completely hopeless' (repeating the same pagination offset); and for writing, 'Gemma 4 wins hands down'. Long-horizon development is openly disputed, with one user calling it 'bad at long horizon development' and another reporting 'no sign of badness'.

Net community verdict in these files: Qwen 3.6, especially the 35B-A3B, is the go-to fast local model for agents, sub-agents, and general assistance, at the cost of trailing newer dense models (Qwen 3.8 27B, Gemma 4) on serious coding, creative writing, and per-mistake reliability. Multimodal/vision capability gets no direct discussion — a vision-model post credits it only as the 'language backbone'. The common forward-looking refrain is to switch to 3.8 27B or await a Qwen4 35B-A3B release.

Pros and cons

Pros

  • Speed is the consistent headline: 'For general agent stuff and speed nothing compares' (DistanceAlert5706); measured reports of 120tk/s at 64k ctx on a 4070 Ti (oxygen_addiction), 131tk/s decode at 100k (oxygen_addiction), 50t/s at 262k ctx on a 12GB 3060 (Miserable-School-665), and 213.3 read / 38.9 write / MTP 55.2 at 35W on a Snapdragon mini PC (WorldlyAd7946).
  • Excellent value on cheap hardware: runs well on 8GB 2060 Super (50 tok/s, 60k ctx - ChrizzAUT), P100s bought for under $180 with 32GB VRAM (Mrinohk), Intel B70 (~100 t/s - PrimeDirective8), and £300/35W Snapdragon boxes (WorldlyAd7946); 'for a sub agent or general purpose that old is gold' (notalentwasted).
  • Proven as an agentic/sub-agent workhorse: 'This model has been my research agent beast for a few months now' (milkipedia); used as fallback for agents that 'perform like subagents -- junior devs' which 'were doing great' (EvolvingDior); 'bigger models making plan, Q36-35 executing, saves a lot of token and time' (feelspeaceman).
  • Retains broad general knowledge that newer coding-focused models traded away: '35B tends to reach for search tools a lot less because it knows more' (PrimeDirective8); '3.8 27b sacrificed general knowledge and reasoning efficiency for coding capability' (Mrinohk); 'it's still smarter than anything else in its class' (milkipedia).
  • Serves as a strong base: 'all 35B A3B models you see are Qwen fine tunes. That's not a bad thing its a good base' (zanar97862); MiniCPM-V 4.7 credits 'Qwen3.6 for providing the language backbone'; derived fine-tunes Ornith and Tiel 'have been doing a decent job for coding' (Sensitive_Song4219).

Cons

  • Mistake rate: 'it makes so many mistakes all the time' — one user who experimented with both sizes concluded 'while 35b of course is a lot faster it's simply not worth using it if you can run 27b' (Naiw80).
  • Coding ceiling: '3.6 35B was never good enough at real coding tasks anyway' (Daniel_H212); 'made the vanilla quite useful for small coding tasks' (Ueberlord) and 'can code small scripts just fine' (PrimeDirective8) — small tasks yes, serious work no.
  • Tool-call parameter handling: 'it's completely hopeless with parameters to the tool call, if you make a paginated tool call it can make 5 calls with the exact same pagination offset etc, when it intended to traverse' (Naiw80).
  • Writing/language trails rivals: 'I prefer Gemma 4 26B for its language skills' and 'for chatting and writing, Gemma 4 wins hands down' (both PrimeDirective8).
  • Long-horizon development is disputed: '3.6 35b is bad at long horizon development' (Mrinohk) vs 'I wouldn't call 3.6 35b bad at long horizon development' (mister2d).
  • The 27B dense variant is slow where the MoE shines: 'this being a dense model (all 27B parameters active all the time) it will be quite slow' (Nixellion); a common quip is that 'One of the best things you can do with Qwen 3.6 27B is to switch to Qwen 3.8 27B' (saltyourhash).

Top quotes

  • “I still run 35ba3b, nothing else better. For general agent stuff and speed nothing compares.”
    DistanceAlert5706 · 6 points positive view on Reddit ↗
  • “This model has been my research agent beast for a few months now. It's so fast, it can run circles around almost anything else locally, and it's still smarter than anything else in its class.”
    milkipedia · 1 points positive view on Reddit ↗
  • “while 35b of course is a lot faster it's simply not worth using it if you can run 27b, as it makes so many mistakes all the time.”
    Naiw80 · 2 points negative view on Reddit ↗
  • “You need to optimize. I'm using llama.cpp with Qwen3.6-35B-A3B-IQ4_XS-4.19bpw and and I'm hitting 120tk/s on a 4070ti and 32GB DDR4 @ 64k context.”
    oxygen_addiction · 14 points positive view on Reddit ↗
  • “Qwen 3.6 35b-a3b Coder with full optimisations (this far) and NPU on a single box: 213.3 read / 38.9 write / MTP 55.2!!!”
    WorldlyAd7946 · 7 points positive view on Reddit ↗
  • “Worse at coding, better at agentic stuff. So it's geared slightly differently. But also I think 3.6 35B was never good enough at real coding tasks anyway.”
    Daniel_H212 · 8 points negative view on Reddit ↗
  • “I wouldn't call 3.6 35b bad at long horizon development. Although I haven't done anything too sophisticated (like tune my GPU kernels), 35B shows no sign of badness in my experience.”
    mister2d · 1 points positive view on Reddit ↗
  • “Qwen3.6 35B can code small scripts just fine, and even larger C# projects if you watch over it.”
    PrimeDirective8 · 3 points positive view on Reddit ↗
  • “And yes, for chatting and writing, Gemma 4 wins hands down.”
    PrimeDirective8 · 1 points negative view on Reddit ↗
  • “One of the best things you can do with Qwen 3.6 27B is to switch to Qwen 3.8 27B”
    saltyourhash · 12 points negative view on Reddit ↗
  • “it's completely hopeless with parameters to the tool call, if you make a paginated tool call it can make 5 calls with the exact same pagination offset etc, when it intended to traverse.”
    Naiw80 · 2 points negative view on Reddit ↗
  • “Why qwen 3.6 27b instead of 3.8?”
    -InformalBanana- · 16 points neutral view on Reddit ↗

Top sample posts

Top 5 of 10 posts by score

FAQ

What is Qwen 3.6 — October 2026's overall community score?
60.7 out of 100, with medium confidence: 10 posts / 375 comments from r/localllama (2026-10, truncated=false), but only 36 comments discuss Qwen 3.6 directly; the strongest signal comes from the dedicated 'Qwen 3.6 35B appreciation post' thread plus the Strata and Snapdragon mini-PC benchmark threads. multimodal_vision has no direct data (null). Sentiment is consistent across threads, with clear pro (speed, agentic use, value) and con (mistakes, coding ceiling, tool-call params) camps.
How was the Qwen 3.6 — October 2026 benchmark collected?
From 10 posts and 375 comments on r/LocalLLaMA sampled over the past month window.
Which categories does the Qwen 3.6 — October 2026 report score?
Intelligence, Coding quality, Instruction following, Long context, Price / value, Speed, Reliability & uptime, Creativity & writing, Multimodal & vision, Agentic & tool use.
What are the main community pros and cons for Qwen 3.6 — October 2026?
Top pros: Speed is the consistent headline: 'For general agent stuff and speed nothing compares' (DistanceAlert5706); measured reports of 120tk/s at 64k ctx on a 4070 Ti (oxygen_addiction), 131tk/s decode at 100k (oxygen_addiction), 50t/s at 262k ctx on a 12GB 3060 (Miserable-School-665), and 213.3 read / 38.9 write / MTP 55.2 at 35W on a Snapdragon mini PC (WorldlyAd7946).; Excellent value on cheap hardware: runs well on 8GB 2060 Super (50 tok/s, 60k ctx - ChrizzAUT), P100s bought for under $180 with 32GB VRAM (Mrinohk), Intel B70 (~100 t/s - PrimeDirective8), and £300/35W Snapdragon boxes (WorldlyAd7946); 'for a sub agent or general purpose that old is gold' (notalentwasted).. Main cons: Mistake rate: 'it makes so many mistakes all the time' — one user who experimented with both sizes concluded 'while 35b of course is a lot faster it's simply not worth using it if you can run 27b' (Naiw80).; Coding ceiling: '3.6 35B was never good enough at real coding tasks anyway' (Daniel_H212); 'made the vanilla quite useful for small coding tasks' (Ueberlord) and 'can code small scripts just fine' (PrimeDirective8) — small tasks yes, serious work no..
When was the Qwen 3.6 — October 2026 data collected?
Collected on November 10, 2026; the report was generated on November 10, 2026.

Collected from public r/LocalLLaMA posts and comments via Reddit JSON API on November 10, 2026.

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