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I Was WRONG About Local LLM vs Claude on M5 macbook pro — TESTED | qwen 3.6 35b, 27b, and gtp oss
Can a $2400 MacBook Pro M5 actually replace Claude? I put three local
LLMs — Qwen3.6-35B-A3B, Qwen3.6-27B, and gpt-oss-20b — head-to-head
against Claude Sonnet 4.6 inside VS Code. The results were not what I
expected.
In this video I run all three open-weight models locally in LM Studio
on the base M5 MacBook Pro, benchmark real tokens-per-second, then ask
each one to build a solar system website. Finally, I open the broken
project in VS Code and let Claude Sonnet 4.6 (via GitHub Copilot) fix
it — and the difference is wild.
If you're a developer thinking about running local AI on Apple Silicon,
a Mac buyer wondering whether the M5 is enough for LLM run locally, or you just
want to see where open models stand against Anthropic's best, this one
is for you.
⏱️ CHAPTERS
🔗 TOOLS USED
- LM Studio (run LLMs locally on Mac): https://lmstudio.ai/
- Ollama (alternative local runner): https://ollama.com/
- Visual Studio Code: https://code.visualstudio.com/
- GitHub Copilot: https://github.com/features/copilot
🤖 MODELS TESTED
- Qwen3.6-35B-A3B (Apache 2.0, Alibaba):
https://huggingface.co/Qwen/Qwen3.6-35B-A3B
- Qwen3.6-27B (Apache 2.0, Alibaba):
https://huggingface.co/Qwen/Qwen3.6-27B
- gpt-oss-20b (Apache 2.0, OpenAI):
https://huggingface.co/openai/gpt-oss-20b
- Claude Sonnet 4.6 (Anthropic):
https://www.anthropic.com/claude/sonnet
💻 MY MACHINE
MacBook Pro M5 chip
14 inch
32gb unified memory (ram)
10 core cpu
10 core gpu
1 tb ssd
(Released Oct 22, 2025 — starting at $1,599)
Apple newsroom: https://www.apple.com/newsroom/2025/10/
📝 NOTES
Qwen3.6-35B-A3B is a sparse Mixture-of-Experts model — only ~3B of
its 35B parameters activate per token, which is exactly why it runs
6–7x faster than the dense Qwen3.6-27B on the same Mac. If you've
been wondering why "bigger" models sometimes feel snappier, that's
the secret.
👋 ABOUT ME
I'm Vikramjit. This channel is where I test AI tools, run local LLMs
on Apple Silicon, and document what actually works for developers.
🔔 If you got value from this, please Like, Subscribe, and tell me in
the comments which model YOU want me to test next. I read every comment.
📬 SOCIALS / CONTACT
- YouTube: https://www.youtube.com/@IamVikramjit
#LocalLLM #MacBookProM5 #Qwen3 #gptoss #ClaudeSonnet #LMStudio
#AppleSilicon #AIcoding #Ollama #OpenSourceAI
Видео I Was WRONG About Local LLM vs Claude on M5 macbook pro — TESTED | qwen 3.6 35b, 27b, and gtp oss канала IamVikramjit
LLMs — Qwen3.6-35B-A3B, Qwen3.6-27B, and gpt-oss-20b — head-to-head
against Claude Sonnet 4.6 inside VS Code. The results were not what I
expected.
In this video I run all three open-weight models locally in LM Studio
on the base M5 MacBook Pro, benchmark real tokens-per-second, then ask
each one to build a solar system website. Finally, I open the broken
project in VS Code and let Claude Sonnet 4.6 (via GitHub Copilot) fix
it — and the difference is wild.
If you're a developer thinking about running local AI on Apple Silicon,
a Mac buyer wondering whether the M5 is enough for LLM run locally, or you just
want to see where open models stand against Anthropic's best, this one
is for you.
⏱️ CHAPTERS
🔗 TOOLS USED
- LM Studio (run LLMs locally on Mac): https://lmstudio.ai/
- Ollama (alternative local runner): https://ollama.com/
- Visual Studio Code: https://code.visualstudio.com/
- GitHub Copilot: https://github.com/features/copilot
🤖 MODELS TESTED
- Qwen3.6-35B-A3B (Apache 2.0, Alibaba):
https://huggingface.co/Qwen/Qwen3.6-35B-A3B
- Qwen3.6-27B (Apache 2.0, Alibaba):
https://huggingface.co/Qwen/Qwen3.6-27B
- gpt-oss-20b (Apache 2.0, OpenAI):
https://huggingface.co/openai/gpt-oss-20b
- Claude Sonnet 4.6 (Anthropic):
https://www.anthropic.com/claude/sonnet
💻 MY MACHINE
MacBook Pro M5 chip
14 inch
32gb unified memory (ram)
10 core cpu
10 core gpu
1 tb ssd
(Released Oct 22, 2025 — starting at $1,599)
Apple newsroom: https://www.apple.com/newsroom/2025/10/
📝 NOTES
Qwen3.6-35B-A3B is a sparse Mixture-of-Experts model — only ~3B of
its 35B parameters activate per token, which is exactly why it runs
6–7x faster than the dense Qwen3.6-27B on the same Mac. If you've
been wondering why "bigger" models sometimes feel snappier, that's
the secret.
👋 ABOUT ME
I'm Vikramjit. This channel is where I test AI tools, run local LLMs
on Apple Silicon, and document what actually works for developers.
🔔 If you got value from this, please Like, Subscribe, and tell me in
the comments which model YOU want me to test next. I read every comment.
📬 SOCIALS / CONTACT
- YouTube: https://www.youtube.com/@IamVikramjit
#LocalLLM #MacBookProM5 #Qwen3 #gptoss #ClaudeSonnet #LMStudio
#AppleSilicon #AIcoding #Ollama #OpenSourceAI
Видео I Was WRONG About Local LLM vs Claude on M5 macbook pro — TESTED | qwen 3.6 35b, 27b, and gtp oss канала IamVikramjit
local llm local llm mac MacBook Pro M5 MacBook Pro M5 AI Apple Silicon LLM Qwen3.6 Qwen3.6 35B Qwen 3.6 vs Claude gpt-oss gpt-oss-20b Claude Sonnet 4.6 Claude vs local LLM LM Studio LM Studio Mac Ollama Mac AI coding VS Code Copilot Claude in VS Code run LLM locally Mac best local LLM 2026 artificial intelligence software developer local llm vs claude code ollama app with local ai mac studio m4 max mac studio ollama llm claude ai hermes ai
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