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Nanbeige4.3-33B model performance compared across three inference engines on MacBook Pro M5 Max

By PulseAugur Editorial · [1 sources] ·

A user on Reddit compared the performance of the Nanbeige4.3-33B model across three different inference engines on a MacBook Pro M5 Max. The comparison focused on prefill and decode speeds, time to first token, latency, and memory usage, with context lengths ranging from 512 to 32K tokens. The results indicated that the Nanbeige4.3-33B model is slow and inefficient with its KV cache, consuming a large amount of memory. Despite its coding capabilities, the user suggested sticking with Qwen models for better performance. AI

IMPACT Provides performance insights for local LLM deployment on Apple Silicon, highlighting trade-offs between models and inference engines.

RANK_REASON User benchmark of a specific model across different inference engines. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Nanbeige4.3-33B model performance compared across three inference engines on MacBook Pro M5 Max

How we ranked this

Signal score
7 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
User benchmark of a specific model across different inference engines. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
infra, model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/DotaMate ·

    Nanbeige4.3-33B Q4 on a MacBook Pro M5 Max, mlx-lm vs llama.cpp vs Kapitsa, Prefill/Decode 512 to 32K range.

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xgaupg/nanbeige4333b_q4_on_a_macbook_pro_m5_max_mlxlm_vs/"> <img alt="Nanbeige4.3-33B Q4 on a MacBook Pro M5 Max, mlx-lm vs llama.cpp vs Kapitsa, Prefill/Decode 512 to 32K range." src="https://preview.redd.it…

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