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32GB of DDR5 now costs $375 – AI shortage continues to squeeze PC building

tomshardware.com
436 points·by papersail·เดือนที่แล้ว·393 comments

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papersail
·24 วันที่ผ่านมา·discuss


  rank  score  age  size   name
  1     62.0   8    -      Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
  2     59.1   55   -      GPT-5.5 (xhigh)
  3     58.5   55   -      GPT-5.5 (high)
  4     57.2   104  -      GPT-5.4 (xhigh)
  5     56.7   20   -      Claude Opus 4.8 (Adaptive Reasoning, Max Effort)
  6     55.5   118  -      Gemini 3.1 Pro Preview
  7     53.1   62   -      Claude Opus 4.7 (Non-reasoning, High Effort)
  8     53.1   132  -      GPT-5.3 Codex (xhigh)
  9     52.5   62   -      Claude Opus 4.7 (Adaptive Reasoning, Max Effort)
  10    51.5   92   -      GPT-5.4 mini (xhigh)
  11    50.9   120  -      Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort)
  12    50.7   1    large  GLM-5.2 (max)
  13    50.1   29   -      Qwen3.7 Max
  14    48.7   188  -      GPT-5.2 (xhigh)
  15    48.1   132  -      Claude Opus 4.6 (Adaptive Reasoning, Max Effort)
  16    47.8   205  -      Claude Opus 4.5 (Reasoning)
  17    47.6   132  -      Claude Opus 4.6 (Non-reasoning, High Effort)
  18    47.5   70   -      Muse Spark
  19    47.5   54   large  DeepSeek V4 Pro (Reasoning, Max Effort)
  20    47.1   58   large  Kimi K2.6
  21    47.1   29   -      Gemini 3.5 Flash (minimal)
  22    46.7   449  -      Gemini 2.5 Pro Preview (Mar' 25)
  23    46.5   211  -      Gemini 3 Pro Preview (high)
  24    46.5   16   -      Qwen3.7 Plus
  25    46.4   120  -      Claude Sonnet 4.6 (Non-reasoning, High Effort)
  26    45.6   5    large  Kimi K2.7 Code
  27    45.6   104  -      GPT-5.4 (low)
  28    45.5   56   large  MiMo-V2.5-Pro
  29    45.1   43   -      GPT-5.5 Instant (May 2026)
  30    45.0   29   -      Gemini 3.5 Flash (high)
  31    44.9   58   -      Qwen3.6 Max Preview
  32    44.7   216  -      GPT-5.1 (high)
  33    44.2   188  -      GPT-5.2 (medium)
  34    44.2   126  large  GLM-5 (Reasoning)
  35    43.9   92   -      GPT-5.4 nano (xhigh)
  36    43.4   71   large  GLM-5.1 (Reasoning)
  37    43.4   16   large  MiniMax-M3
  38    43.2   54   large  DeepSeek V4 Pro (Reasoning, High Effort)
  39    43.0   188  -      GPT-5.2 Codex (xhigh)
  40    42.9   76   -      Qwen3.6 Plus
  41    42.9   205  -      Claude Opus 4.5 (Non-reasoning)
  42    42.6   182  -      Gemini 3 Flash Preview (Reasoning)
  43    42.2   99   -      Grok 4.20 0309 (Reasoning)
  44    42.1   56   large  MiMo-V2.5
  45    41.9   91   large  MiniMax-M2.7
  46    41.4   91   -      MiMo-V2-Pro
  47    41.3   121  large  Qwen3.5 397B A17B (Reasoning)
  48    41.0   48   -      Grok 4.3 (high)
  49    40.5   71   -      Grok 4.20 0309 v2 (Reasoning)
  50    40.5   342  -      Grok 4
  51    39.8   54   large  DeepSeek V4 Flash (Reasoning, High Effort)

A longer curated list based on kristopolous’ list, with more models included. For each model, I kept only the two highest-scoring entries. I used DeepSeek V4 Flash as the cutoff, since I consider it the lowest acceptable model that is still locally deployable.
papersail
·24 วันที่ผ่านมา·discuss


  score  age  size   name
  62.0   8    -      Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
  59.1   55   -      GPT-5.5 (xhigh)
  58.5   55   -      GPT-5.5 (high)
  57.2   104  -      GPT-5.4 (xhigh)
  56.7   20   -      Claude Opus 4.8 (Adaptive Reasoning, Max Effort)
  56.2   55   -      GPT-5.5 (medium)
  55.5   118  -      Gemini 3.1 Pro Preview
  53.1   132  -      GPT-5.3 Codex (xhigh)
  53.1   62   -      Claude Opus 4.7 (Non-reasoning, High Effort)
  52.5   62   -      Claude Opus 4.7 (Adaptive Reasoning, Max Effort)
  52.1   55   -      GPT-5.5 (low)
  51.5   92   -      GPT-5.4 mini (xhigh)
  50.9   120  -      Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort)
  50.7   1    large  GLM-5.2 (max)
  50.1   29   -      Qwen3.7 Max
  48.7   188  -      GPT-5.2 (xhigh)
  48.6   55   -      GPT-5.5 (Non-reasoning)
  48.1   132  -      Claude Opus 4.6 (Adaptive Reasoning, Max Effort)
  47.8   205  -      Claude Opus 4.5 (Reasoning)
papersail
·25 วันที่ผ่านมา·discuss
I had similar doubts. I think expectations differ because the workload differs. For small scripts, glue code, or simple CRUD changes, smaller models such as Qwen3.6-27B can work wonders than they do on a larger, messier code base.
papersail
·29 วันที่ผ่านมา·discuss
I'm not sure I would put too much weight on DeepSWE as a benchmark, given that GPT-5.4-mini ended up close to Opus 4.6 there.
papersail
·เดือนที่แล้ว·discuss
My usual workflow is GPT-5.5 for planning, DeepSeek V4 Flash for milestones implementation, then GPT-5.5 again for review. It has worked pretty well so far.
papersail
·เดือนที่แล้ว·discuss
I used to collect old hardware and try to install NetBSD/OpenBSD on them. For me, a lot of the fun was the "challenge accepted" aspect. Getting them to boot and work on some weird and obsolete machines felt like winning a small battle.