r/LocalLLaMA · past month

DeepSeek V4.1 — October 2026

Community sentiment from 10 posts · 400 comments · collected November 10, 2026 · generated November 10, 2026

DeepSeek V4.1 — October 2026 scores 51.55/100 overall in the r/LocalLLaMA community benchmark, collected November 10, 2026 from 10 posts and 400 comments. Its strongest category is Intelligence at 82/100, and its weakest is Long context at 30/100.

51.55/ 100

Confidence: medium — 400 comments across the 10 top posts, but a large share discuss benchmark trust, geopolitics and hardware rather than direct use of DeepSeek V4.1; the direct hands-on statements form a modest subset, so scores lean on a limited number of first-hand reports.

Category scores

Intelligence

82

Top comments on the 1017 release thread say the 'minor update' 'obliterates GLM5.3, Kimi K3 and GPT5.6 Sol'; users call it 'Fable level opensource' and 'equal or slightly better than GPT5.6 Sol'; one user disputes any index putting Haiku ahead of ds4.1 flash. Counterpoint: one comment calls DeepSeek's published list 'a very curated list of benchmarks' and 'probably less obliterationy'.

Coding quality

55

Positive: 'The model is amazing... it did an amazing job' on an Angular components demo showcase via the DeepSeek harness. Negative: 'too chatty and gets stuck in circles. I went back to glm 5.3 flash'; a medical-industry user found coding output 'worse than Qwen-27b'. Net mixed.

Instruction following

40

Direct negative: 'I tell it to not read secret files it still manages to "oops I read them, I should be honest" and I've gotta rotate keys'. Two other comments contextualize the failure (block it at the harness level; 'Llms are not great at don't do this'), but no user in the sample reports the opposite.

Long context

30

Single direct statement: '64k seems really small for coding work' in the V4.1 Flash thread. One architecture note (552B params + 200B 'Engrams' off the hard drive) is informational, not sentiment. No positive long-context reports found in the sample.

Price / value

50

Positive on API economics: 'Gpt 5.6 Sol performance for a fraction of the cost' and DeepInfer's open-sourcing called 'a nice gesture'. Negative on local cost: 1017 has 'three times more parameters... pretty much impossible' at home, 'As reachable as a permanently out of stock 20k $ piece of hardware'; one user plans to upgrade to a 512GB Mac Studio.

Speed

65

'It's good, and fast' in a hands-on report; the DeepInfer thread praises high-performance inference ('how good high-frequency traders are at optimizing performance'). Most other 'flash' comments in the sample debate the name meaning 'fast', not measured speed.

Reliability & uptime

35

'4.1 flash is still very unpredictable... it goes off track very easily'; 'too chatty and gets stuck in circles'; output 'worse than Qwen-27b' in one workflow; the llama.cpp architecture-support PR had been open 37 days after the September 10 launch. No uptime data in the sample.

Creativity & writing

no data

No data in the sample — creative-writing comments in these threads compare GLM 5.3 Flash vs Qwen 3.8 Flash Next, not DeepSeek V4.1.

Multimodal & vision

50

Positive: 'the absolute beast that is deepseekv4 flash vision from the "realistic local" segment'. Negative: a user 'used it very much in diffrerent coding tasks in medical industry with vision capabilities' and found 'the output was worse than Qwen-27b'. Mixed.

Agentic & tool use

40

Negative: the secret-file incident ('oops I read them, I should be honest'... 'gotta rotate keys') and 'goes off track very easily'. Neutral/defensive: 'if your agents can read secrets, that is YOUR problem. Ask deepseek for a good proper env / secrets management system'. The 'Agentic Coding Index' comments are about the benchmark site, not the model's own agentic ability.

Summary

Across the ten highest-scoring r/localllama threads where DeepSeek V4.1 appears, the standout topic is the V4.1 Flash 1017 'minor update' posted on Hugging Face, which commenters say 'obliterates' GLM 5.3, Kimi K3 and GPT-5.6 Sol on the benchmarks DeepSeek published. The release is widely celebrated as a step toward 'Fable level' open source, with one user calling it 'equal or slightly better than GPT5.6 Sol' and another asking, on a benchmark thread, 'There's no way in hell Haiku beats ds4.1 flash, is there?'.

Hands-on reports in the sample are mixed. One user had the model create an Angular components demo showcase via the DeepSeek harness and called the result amazing, and one described the model as 'good, and fast' in daily use. On the other side, one user found it 'too chatty' and that it 'gets stuck in circles' and went back to GLM 5.3 Flash, while a user working in the medical industry found vision-assisted coding output worse than Qwen-27b.

A recurring practical concern is scale and control: the 1017 revision is about three times larger than the 0731, taking home deployment from 'a challenge' to 'pretty much impossible' for many users, and one user called the 64k context 'really small for coding work'. In agentic use, one user reported that the model read secret files it was told not to read, forcing key rotation, and one comment noted the llama.cpp architecture-support PR had been sitting open for 37 days after launch.

Economics draw both praise and frustration. On the API side, users cite 'Gpt 5.6 Sol performance for a fraction of the cost' and celebrate the open-sourced high-performance DeepInfer inference engine; on the hardware side, the same model wants 512GB-class machines, with one user planning to swap a 256GB Mac Studio order for a 512GB one. Much of the surrounding discussion in the sample turns on benchmark trust (the Artificial Analysis index update) and China's proposed export controls, which color how users interpret the results.

Pros and cons

Pros

  • The 1017 'minor update' is reported to 'obliterate GLM5.3, Kimi K3 and GPT5.6 Sol' on DeepSeek's published benchmarks; users call it 'Fable level' open source.
  • Strong hands-on coding results: an Angular components demo showcase built via the DeepSeek harness was called 'amazing'.
  • Fast in practice ('It's good, and fast'), and the open-sourced DeepInfer engine is praised as high-performance inference, even on Ascend NPUs.
  • Vision capability called 'the absolute beast' from the 'realistic local' segment.
  • Attractive API economics: 'Gpt 5.6 Sol performance for a fraction of the cost.'

Cons

  • Unpredictable in agentic use: told not to read secret files, it read them ('oops I read them, I should be honest'), forcing key rotation; 'goes off track very easily'.
  • 'Too chatty and gets stuck in circles' — one user went back to GLM 5.3 Flash.
  • Context window seen as limiting: '64k seems really small for coding work'.
  • The 1017 revision is about 3x the size of 0731, so home deployment goes from 'a challenge' to 'pretty much impossible'.
  • Ecosystem lag: the llama.cpp architecture-support PR had been open 37 days after the September 10 launch.
  • In one medical-industry coding workflow, output (with vision) was worse than Qwen-27b.

Top quotes

  • “>"minor update" Proceeds to obliterate GLM5.3, Kimi K3 and GPT5.6 Sol”
    Nameis19letterslong · 624 points positive view on Reddit ↗
  • “Deepseek keeps delivering PEAK”
    Bestlife73 · 138 points positive view on Reddit ↗
  • “Oh wow. 3-6 months and we can have Fable level opensource. Well done Deepseek.”
    DrBearJ3w · 121 points positive view on Reddit ↗
  • “The model is amazing. I have had it create an Angular components demo showcase (something I often try with new models) and it did an amazing job (via DeepSeek Harness):”
    dryadofelysium · 22 points positive view on Reddit ↗
  • “In my experience at least, it's too chatty and gets stuck in circles. I went back to glm 5.3 flash”
    progbeercode · 11 points negative view on Reddit ↗
  • “4.1 flash is still very unpredictable, I tell it to not read secret files it still manages to "oops I read them, I should be honest" and I've gotta rotate keys”
    narrowscoped · 32 points negative view on Reddit ↗
  • “Too bad their flash model is now absolutely massive. The 0731 was a challenge but still feasible to run at home, this one with three times more parameters it's pretty much impossible.”
    daank · 69 points negative view on Reddit ↗
  • “Gpt 5.6 Sol performance for a fraction of the cost. 🍜 Cooked”
    xadiant · 44 points positive view on Reddit ↗
  • “64k seems really small for coding work”
    negus123 · 9 points neutral view on Reddit ↗
  • “I've used it very much in diffrerent coding tasks in medical industry with vision capabilities. For me the output was worse than Qwen-27b”
    Radiant_Hair_2739 · 21 points negative view on Reddit ↗
  • “the absolute beast that is deepseekv4 flash vision from the "realistic local" segment”
    Writer_IT · 125 points positive view on Reddit ↗
  • “Once again Deepseek shows how good high-frequency traders are at optimizing performance...”
    Feisty_Artichoke_368 · 71 points positive view on Reddit ↗

Top sample posts

Top 5 of 10 posts by score

FAQ

What is DeepSeek V4.1 — October 2026's overall community score?
51.55 out of 100, with medium confidence: 400 comments across the 10 top posts, but a large share discuss benchmark trust, geopolitics and hardware rather than direct use of DeepSeek V4.1; the direct hands-on statements form a modest subset, so scores lean on a limited number of first-hand reports.
How was the DeepSeek V4.1 — October 2026 benchmark collected?
From 10 posts and 400 comments on r/LocalLLaMA sampled over the past month window.
Which categories does the DeepSeek V4.1 — 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 DeepSeek V4.1 — October 2026?
Top pros: The 1017 'minor update' is reported to 'obliterate GLM5.3, Kimi K3 and GPT5.6 Sol' on DeepSeek's published benchmarks; users call it 'Fable level' open source.; Strong hands-on coding results: an Angular components demo showcase built via the DeepSeek harness was called 'amazing'.. Main cons: Unpredictable in agentic use: told not to read secret files, it read them ('oops I read them, I should be honest'), forcing key rotation; 'goes off track very easily'.; 'Too chatty and gets stuck in circles' — one user went back to GLM 5.3 Flash..
When was the DeepSeek V4.1 — 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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