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VeriLoop E2, a 27B open-weight reasoning model, is now available

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ModelScope announces VeriLoop E2, a 27B open-weight model built on Qwen3.8-27B with a 262K native context window. The company reports 76.2% on SWE-bench Pro, 88.8% on Terminal-Bench 2.1, 98.3% on AIME 2026, and 93.9% on GPQA Diamond. Model weights and public inference utilities are released under Apache 2.0, while the production VeriLoop Harness is not included.

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The post names the open-weight base model, the verifier-governed training loop, and the benchmark results, so readers can check the claimed gains against comparison models.

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VeriLoop E2 is now available, bringing verifier-governed reasoning to code, mathematics, and physics in a 27B open-weight model.
🤖 https://modelscope.ai/models/tsinghua-sigs-robot-lab/VeriLoop-E2

🏆 The evaluated E2 system scores 76.2% on SWE-bench Pro, 88.8% on Terminal-Bench 2.1, 98.3% on AIME 2026, 93.9% on GPQA Diamond, and 89.6% on Apex 2025.
🔁 VeriLoop-Governed Recurrence proposes candidates, verifies them externally, and commits only improvements without regression.
🧪 Two evidence-backed scientific demonstrations cover a 67.35% Riemann ζ zero-proportion certificate and Asymptotic Graviton Tomography. Neither claims to solve the underlying open problem.
📚 Built on Qwen3.8-27B with a 262K native context window and OpenAI-compatible vLLM serving validated at 131K.
📜 Model weights and public inference utilities: Apache 2.0. The production VeriLoop Harness is not included, and the scientific artifacts carry separate terms.

Source: ModelScope · x.comPublished · added here

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