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to think that o3-mini was my choice model for a long time, and now gpt-oss:20...

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to think that o3-mini was my choice model for a long time, and now gpt-oss:20B is basically equivalent and runs on my laptop 🤯
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comparison
Grouped bar chart with five subplots comparing model accuracy across different tasks and benchmarks. Each subplot shares the same x-axis: models o3, o3-mini, o4-mini, gpt-oss-120b, and gpt-oss-20b. Color-coded bars represent different models. Top row: 1. AIME 2024 (Competition Math, With Tools) • o3: 95.2% • o3-mini: 87.3% • o4-mini: 98.7% • gpt-oss-120b: 96.6% • gpt-oss-20b: 96.0% 2. AIME 2025 (Competition Math, With Tools) • o3: 98.4% • o3-mini: 86.5% • o4-mini: 99.5% • gpt-oss-120b: 97.9% • gpt-oss-20b: 98.7% 3. GPQA Diamond (PhD Science Questions, Without Tools) • o3: 83.3% • o3-mini: 77.0% • o4-mini: 81.4% • gpt-oss-120b: 80.1% • gpt-oss-20b: 71.5% Bottom row: 4. HLE (Expert-Level Questions) • o3 (tools): 24.9% • o3-mini (no tools): 13.4% • o4-mini: 17.7% • gpt-oss-120b (tools): 19.0% • gpt-oss-120b (no tools): 14.9% • gpt-oss-20b (tools): 17.3% • gpt-oss-20b (no tools): 10.9% 5. MMLU (College-level Exams) • o3: 93.4% • o3-mini: 87.0% • o4-mini: 93.0% • gpt-oss-120b: 90.0% • gpt-oss-20b: 85.3% Overall, o4-mini performs strongest on AIME and MMLU. o3 has the highest HLE accuracy with tools. GPT-based models trail behind across most tasks.
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