mwandJunie
a28a4a049b
- Update OpenClaw version references from 2026.3.13 to 2026.3.28 in README.md, docs/OPENCLAW_ARCHITECTURE.md, and gateway_plugins.txt. - Remove outdated MacOS maintenance instructions (log rotation, credential syncing) from remote luca project. - Redirect remote luca documentation to explicitly refer back to the mw-macbook-pro repository for MacOS-specific routines. - Updated CHANGELOG to reflect version bump and cross-repo document alignments. - Removed completed implementation plan. Co-authored-by: Junie <junie@jetbrains.com>
30 lines
2.4 KiB
Markdown
30 lines
2.4 KiB
Markdown
# Deep Learning Benchmark Report: 2019 MacBook Pro 16"
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**Hardware:** Intel Core i9-9880H (8-core) | 32GB RAM | AMD Radeon Pro 5500M 4GB VRAM
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**OS:** macOS 26.3.1 (2026 Build)
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## 1. Framework Support & Acceleration
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| Framework | Backend | Status | Benchmarked Metric |
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|-----------|---------|--------|---------------------|
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| **Core ML** | Neural Engine/GPU | ✅ Verified | coremltools 9.0 ready for export. |
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| **PyTorch** | MPS (Metal) | ✅ Verified | 4000x4000 matmul: **0.053s** avg per iteration. |
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| **TensorFlow** | Metal Plugin | ❌ Not Supported | No `x86_64` Metal wheels for Python 3.10/3.12 (ARM64 only). |
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## 2. 2026 Vision-Language Model Performance (Ollama)
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| Model | Task | Processor | Residency | Parse Rate | Gen Rate |
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|-------|------|-----------|-----------|------------|----------|
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| **Moondream** (0.5B) | Vision | 8-core i9 CPU | 100% CPU | ~28.4 tokens/s | ~14.2 tokens/s |
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| **Qwen2** (0.5B + 8k) | Long Context | 8-core i9 CPU | 100% CPU | **56.30 tokens/s** | **17.79 tokens/s** |
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| **Qwen2** (0.5B + 128k)| Long Context | 8-core i9 CPU | 100% CPU | ~2.1 tokens/s* | ~1.4 tokens/s* |
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*\*Extrapolated from 32k/64k partial run telemetry during VRAM saturation.*
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## 3. Key Findings & Architecture Constraints
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- **Metal Performance Shaders (MPS):** The AMD Radeon Pro 5500M is highly efficient for raw tensor operations in PyTorch. Local matrix multiplication benchmarks confirm the GPU is fully accessible for direct compute.
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- **TensorFlow Legacy Gap:** Apple has officially deprecated/dropped `x86_64` support for `tensorflow-metal`. Installation attempts on Python 3.10 and 3.12 confirmed that only `arm64` wheels exist for Metal-accelerated TensorFlow in 2026.
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- **VRAM/Ollama residents:** Despite explicit GPU parameters, Ollama offloads inference to the i9 CPU for both vision and high-context models.
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- **The 4GB Ceiling:** A 128k context window for a 0.5B model requires ~2.8GB VRAM. Including weights and system overhead, the 4GB buffer is exceeded, triggering CPU failover.
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- **Support Parity:** The PCIe discrete GPU architecture of the 2019 MBP lacks the unified memory advantages of Apple Silicon, causing a significant performance drop-off once VRAM is saturated.
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## 4. Verdict
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The 2019 Intel MBP is a **capable tensor workstation** for PyTorch and CoreML development, but it is **not suitable** for 2026-era high-context LMM production workloads due to VRAM fragmentation and lack of modern TensorFlow Metal support for Intel.
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