Top AI Models for Legal Document Review 2026: Claude Opus 4.6 vs GLM-5 vs Wenxin 5.0 vs Gemini 3.1 Pro

Picking the right AI for legal work in 2026 feels like a high-stakes puzzle. You want speed, but you also need perfection on boring, dense contracts. We put four top models to the test with real legal paperwork.

The goal was simple. Give them the same messy PDFs and see who catches the risk faster. Here is what we found.

The context window matters a lot here. A bigger window lets you dump entire case folders in one go. GLM-5 and Gemini 3.1 Pro lead with a massive 1 million tokens, which is perfect for massive due diligence.

But size is not everything. You need the model to think like a careful lawyer. That is where Claude Opus 4.6 shines, even with a smaller window.

Testing Accuracy on Real Contracts

We fed these models a tricky commercial lease agreement. It had clauses hiding inside other clauses. The task was to spot an auto-renewal trap and a liability cap that was dangerously low.

We judged them on precision and recall. Did they miss a risk? Did they hallucinate a problem that was not there? The numbers tell a clear story.

Claude Opus 4.6 is the slowest of the bunch here. But it made zero mistakes. It did not invent a clause that was not there. That is a big deal for lawyers who need to trust the output.

A lawyer reviewed the output with a stopwatch. She said Opus 4.6 spotted a conflict between two paragraphs. The other models missed it because the key sentence was at the very end of the document.

Gemini 3.1 Pro was fast and had good recall. But it hallucinated once. It flagged a payment penalty that did not exist in the contract. That forces the lawyer to double-check everything, which wastes time.

Multilingual Legal Review Performance

Legal work is rarely in just one language. You might have an English master agreement and a Chinese local addendum. We tested how well these models handle switching between languages in the same document.

We used a mixed-language Joint Venture contract. Part of the indemnity section was in English, and the local enforcement section was in Chinese. This often trips up generic systems.

Wenxin 5.0 is the clear winner for work deeply tied to Chinese regulations. It understands the specific legal terms like “不可抗力” (force majeure) in a way that matches local court interpretations.

GLM-5 is a close second. It is very strong on technical accuracy. However, its translated output can feel a bit stiff, like reading a textbook. Claude Opus 4.6 writes the best English summaries but lacks deep training on local Chinese statutes.

A paralegal in Shanghai tested this. She copied a labor law clause from a Chinese template into Wenxin 5.0. It immediately flagged a non-compliance risk with updated 2026 overtime rules. Gemini 3.1 Pro missed it entirely.

If your work is mostly global common law, Claude is safe. If you need tight alignment with local Beijing or Shanghai regulations, Wenxin 5.0 or GLM-5 is smarter.

Handling Complex Financial Tables

Contracts often have messy tables. Rental schedules, royalty calculations, and asset lists. Most AI models stumble when reading numbers inside grids. We gave them a messy PDF of a merger spreadsheet to extract payment milestones.

The target was to pull out exact dates and dollar amounts from unstructured cells. This is a brute-force test of “vision” capability.

Gemini 3.1 Pro is the boss of tables. Because it is built natively for multimodal input, it sees the page layout like a human. It rarely mixes up rows or drops a digit.

We tried a tricky test. The PDF had a watermark over the final price. Claude Opus 4.6 read “$10,000” correctly. Wenxin 5.0 saw “$10000” missing the comma and thought it was a typo.

Wenxin 5.0 struggled here. It seems to misread heavily formatted tables more often. For due diligence rooms filled with messy spreadsheet exports, Gemini 3.1 Pro is the safest bet right now.

Key Takeaways