Unverified60% confidenceBenchmarkExact time
Local inference is constrained by the user's hardware: a 7B-parameter quantized model (such as the Q4 version of Llama 3 8B) has a file size of approximately 4–5 GB, can reach 20–40 tokens per second on a Mac with an Apple M-series chip, and may drop to 3–5 tokens per second on a laptop with only an integrated GPU and 8 GB of RAM.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
9/1/2026
First Seen
Valid until: 11/30/2026
Sources
Related Entities
Related Claims
VerifiedThe memory bandwidth of Apple M-series chips can reach 200–800 GB/s (depending on the specific model)79% similarUnverifiedOllama local deployment measured throughput: MacBook M2 16GB approximately 15 tokens/second, RTX 3060 12GB approximately 45, RTX 4090 24GB approximately 70, 8GB laptop approximately 578% similarUnverifiedA developer connected an iPhone 17 Pro Max to a 24GB-memory M4 Pro MacBook via a 10 Gb/s USB-C cable, using the phone as a second GPU to share the computational load for a locally running Qwen 3.8 27B (IQ4_XS quantization) model.78% similarUnverifiedUsers can run local models with 7B to 70B parameters on consumer-grade GPUs (such as an RTX 4090 with 24GB of VRAM) or on Apple Silicon devices with unified memory.78% similarVerifiedAfter 4-bit quantization, Llama 3.3 70B has a model size of approximately 40 GB and can run on a Mac Studio with 64 GB of memory or a single professional GPU with 48 GB of VRAM.77% similar
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