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Spreadsheet-RL-8B is the RL-trained 8B spreadsheet agent checkpoint from Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning. It starts from Qwen/Qwen3-8B and is post-trained with outcome-based reinforcement learning in Spreadsheet Gym, a multi-turn Microsoft Excel environment with spreadsheet-native tools, sandboxed code execution, and Excel-based recalculation rewards.

This checkpoint is intended to be used with the Spreadsheet-RL agent harness and tool environment. Loading it as a plain chat model can be useful for inspection, but it will not reproduce the reported results without Spreadsheet Gym, the tool set, and the reward/evaluation pipeline.

For full details, please see the paper. The released 8B checkpoint uses:

Spreadsheet-RL improves Qwen3-8B through spreadsheet-native interaction design, comprehensive tool access, and RL post-training.

The released step-35 checkpoint is the best observed checkpoint and improves the full-harness pre-RL result by 5.6 percentage points.

The corresponding 4B release starts from Qwen/Qwen3-4B-Thinking-2507. Its 2507 checkpoint postdates the original Qwen3 series, including Qwen/Qwen3-8B, so model size and base-checkpoint vintage are confounded. Under the full Spreadsheet-RL harness, the 8B model trails the 4B model both before RL (16.7 versus 19.3) and after RL (22.3 versus 23.4); this should not be interpreted as a clean size-only comparison. Instead, the 8B gain from 16.7 to 22.3 shows that Spreadsheet-RL remains effective at a larger model scale, and we release the post-RL checkpoint to make that scaling result reproducible.

Install the standard Transformers stack and load the checkpoint:

For task evaluation and agent rollouts, use the full Spreadsheet-RL codebase with the released dataset and Spreadsheet Gym:

The default training/evaluation harness is maintained in the code repository under configs/, scripts/, reward/, and verl/.