Unverified50% confidenceDecision RuleExact time
For running models within 30 billion parameters, the 64G version is enough; only when a parameter scale above 100 billion is needed is it worth paying 9,000 yuan more for the 128G version.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/25/2026
First Seen
Valid until: 1/23/2027
Sources
64GB Laptop Running LLMs: Only 46.7GB Actually Usable
bilibiliAIPC煜森10/23/2026
Related Entities
Related Claims
UnverifiedThe official model parameter upper limit listed for the 128G version is 120 billion parameters.79% similarUnverifiedRunning an open-source model at the 70-billion-parameter scale requires at least approximately 140GB of VRAM in FP16 precision, i.e., 8 H100s in parallel.70% similarUnverifiedThe open-source project claims that the 125B model quantized with IQ3 can run on consumer-grade hardware consisting of a 12GB VRAM GPU plus 32GB or more of CPU memory.69% similarUnverifiedRunning a 27B model on 8GB of VRAM relies on low-bit quantization and partial parameter offloading strategies, which may limit inference speed; users prioritizing speed are advised to choose a version with 16GB or more of VRAM.67% similar
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