@Lekomio: Nenne mir ein Produkt wo das so war.
Ja es wurden viele Produkte (und Services) eingestellt. Dies geschah immer mit einer Ankundügung Support läuft nach einer Zeit nun mal aus. Das hast du bei sehr vielen Produkten. Das ist kein Google eigenes Problem. Das nennt sich Kostenrechnung. Wenn du auf Software anspielst. Dann sollte auch erwähnt werden das vieles davon kostenlos war und auch dazu noch Experimente.

Quote from: AI+ on May 08, 2026, 09:42:00(The number of CPU threads doesn't matter for running AI (aka inferencing) (4 threads pretty much tops-out a dual-channel PC))

Correction: >4 threads improve MTP LLMs speed:
Using Qwen3.6-27B-UD-Q4_K_XL.gguf (download: huggingface.co/unsloth/Qwen3.6-27B-MTP-GGUF):
./llama.cpp/build/bin/llama-server --models-preset 'LLMs.ini' --threads 8 --models-max 1 --no-models-autoload -np 1 --no-warmup --chat-template-kwargs '{"preserve_thinking": true}' --no-mmproj --offline --no-mmap --spec-type draft-mtp --spec-draft-n-max 2

• 4 threads: ~8.7 tokens per second
• 6 threads: ~10.8 tokens per second
• 8 threads: ~12 tokens per second
• beyond 8 threads the tokens per second number doesn't increase

Source: reddit/"PSA: Test your "threads" argument in llama.cpp (+80% performance in my case)"

Quote from: may not adequate for AI on May 06, 2026, 09:06:53(The number of CPU threads doesn't matter for running AI (aka inferencing) (4 threads pretty much tops-out a dual-channel PC))

Correction: >4 threads improve MTP LLMs speed:
Using Qwen3.6-27B-UD-Q4_K_XL.gguf (download: huggingface.co/unsloth/Qwen3.6-27B-MTP-GGUF):
./llama.cpp/build/bin/llama-server --models-preset 'LLMs.ini' --threads 8 --models-max 1 --no-models-autoload -np 1 --no-warmup --chat-template-kwargs '{"preserve_thinking": true}' --no-mmproj --offline --no-mmap --spec-type draft-mtp --spec-draft-n-max 2

• 4 threads: ~8.7 tokens per second
• 6 threads: ~10.8 tokens per second
• 8 threads: ~12 tokens per second
• beyond 8 threads the tokens per second number doesn't increase

Source: reddit/"PSA: Test your "threads" argument in llama.cpp (+80% performance in my case)"

Quote from: Same on May 13, 2026, 10:07:22(The number of CPU threads doesn't matter for running AI (aka inferencing) (4 threads pretty much tops-out a dual-channel PC))

Correction: >4 threads inr MTP:
Using Qwen3.6-27B-UD-Q4_K_XL.gguf (download: huggingface.co/unsloth/Qwen3.6-27B-MTP-GGUF):
./llama.cpp/build/bin/llama-server --models-preset 'LLMs.ini' --threads 8 --models-max 1 --no-models-autoload -np 1 --no-warmup --chat-template-kwargs '{"preserve_thinking": true}' --no-mmproj --offline --no-mmap --spec-type draft-mtp --spec-draft-n-max 2

• 4 threads: ~8.7 tokens per second
• 6 threads: ~10.8 tokens per second
• 8 threads: ~12 tokens per second
• beyond 8 threads the tokens per second number doesn't increase

Source: reddit/"PSA: Test your "threads" argument in llama.cpp (+80% performance in my case)"

The replay is meant for the following, not for "I'm not impressed. The M..":

Quote from: Very slow for AI on May 18, 2026, 12:04:34(The number of CPU threads doesn't matter for running AI (aka inferencing) (4 threads pretty much tops-out a dual-channel PC))

Quote from: Woof on May 25, 2026, 15:38:16I'm not impressed. The Mac Mini M5 is about to come out, which will be cheaper and faster.

Correction: >4 threads inr MTP:
Using Qwen3.6-27B-UD-Q4_K_XL.gguf (download: huggingface.co/unsloth/Qwen3.6-27B-MTP-GGUF):
./llama.cpp/build/bin/llama-server --models-preset 'LLMs.ini' --threads 8 --models-max 1 --no-models-autoload -np 1 --no-warmup --chat-template-kwargs '{"preserve_thinking": true}' --no-mmproj --offline --no-mmap --spec-type draft-mtp --spec-draft-n-max 2

• 4 threads: ~8.7 tokens per second
• 6 threads: ~10.8 tokens per second
• 8 threads: ~12 tokens per second
• beyond 8 threads the tokens per second number doesn't increase

(Initial source in below post..dumb spam protection says no phon* numbers allowed)