Legal teams now face a flood of documents. AI models that read, tag, and summarize contracts have become essential tools. In 2026, four models lead this space: Claude Opus 4.6, GLM-5, Wenxin 5.0, and Gemini 3.1 Pro.
Each model serves different legal markets. Some excel at Western common law. Others handle Chinese regulatory language with native fluency. Picking the right one saves firms thousands of hours and reduces risk.
Below, we compare them across key dimensions that matter to lawyers, compliance officers, and legal tech buyers.
| Model | Maker | Max Context | Primary Legal Market | Release Date |
|---|---|---|---|---|
| Claude Opus 4.6 | Anthropic | 500K tokens | US, UK, EU common law | March 2026 |
| GLM-5 | Zhipu AI | 256K tokens | China, Southeast Asia | January 2026 |
| Wenxin 5.0 | Baidu | 200K tokens | Mainland China | February 2026 |
| Gemini 3.1 Pro | Google DeepMind | 2M tokens | Global, multilingual | April 2026 |
A New York law firm tested Claude Opus 4.6 on 800-page merger agreements. The model spotted inconsistent termination clauses that junior associates missed. It finished the review in 12 minutes.
Context window size matters deeply in legal work. A single M&A deal can span thousands of pages. Models with larger windows avoid chunking errors that break logical connections across sections.
Models that see the full document at once make fewer mistakes on cross-references and definitions.
Window size is now a key buying factor for legal departments reviewing complex deals.
Legal accuracy requires more than raw size. Models must understand specialized terminology and regional rules. The next table shows how each model scores on benchmarks that mirror real legal tasks.
| Model | LegalBench Score | BAR Exam Pass Rate | Contract Clause Detection (F1) | Multilingual Legal (CEPS) |
|---|---|---|---|---|
| Claude Opus 4.6 | 94.2% | 92% | 0.91 | 78% |
| GLM-5 | 86.7% | 81% | 0.84 | 88% |
| Wenxin 5.0 | 83.4% | 78% | 0.81 | 85% |
| Gemini 3.1 Pro | 93.8% | 91% | 0.89 | 91% |
LegalBench tests reasoning across U.S. legal tasks. CEPS measures Chinese-English legal document understanding.
A Shanghai corporate team used GLM-5 to review 500 Chinese supply contracts. The model flagged force majeure gaps in 94% of agreements. It understood local court precedents that foreign models overlooked.
Asian legal markets often need models trained on local case law. GLM-5 and Wenxin 5.0 build on Chinese regulatory databases that Western models rarely access. This creates a real performance gap for firms operating in China.
| Capability | Claude Opus 4.6 | GLM-5 | Wenxin 5.0 | Gemini 3.1 Pro |
|---|---|---|---|---|
| Redline generation | Yes, native | Via plugin | Via plugin | Yes, native |
| Regulatory citation check | US, EU, UK | China, ASEAN | China only | Global |
| Privilege detection | High accuracy | Moderate | Moderate | High accuracy |
| Contract playbook automation | Full support | Limited | Limited | Full support |
| Voice-to-text deposition | No | No | Yes, Baidu suite | Planned Q3 2026 |
Workflow integration separates tools that lawyers actually use from shelf-ware. Native redlining lets lawyers compare versions without exporting files. Privilege detection prevents costly discovery mistakes.
Models that plug directly into Microsoft Word, iManage, or local court systems see higher adoption.
Legal teams abandon even smart tools that require extra login steps or file format wrestling.
Pricing and deployment options also shape decisions. Some firms need on-premise setup for client confidentiality. Others prefer cloud flexibility. The following table breaks down these practical factors.
| Factor | Claude Opus 4.6 | GLM-5 | Wenxin 5.0 | Gemini 3.1 Pro |
|---|---|---|---|---|
| API pricing (per 1M tokens) | $18 input / $90 output | $8 input / $24 output | $6 input / $18 output | $12 input / $48 output |
| On-premise option | Enterprise only | Yes, with license | Yes, with license | Enterprise only |
| Data residency guarantee | US, EU | China | China | US, EU, Singapore |
| SSO / audit logs | Full | Basic | Full | Full |
| Custom fine-tuning | Limited beta | Available | Available | Available |
A German bank chose Gemini 3.1 Pro for its EU data residency requirement. Their compliance head said moving data to US or Chinese servers would violate GDPR Article 44. The Singapore node option sealed the deal for their Asian branches too.
Cost gaps are stark. Wenxin 5.0 costs roughly one-fifth of Claude Opus 4.6 for output tokens. Chinese firms running high-volume contract reviews find this decisive. Western firms handling cross-border deals often pay premium prices for multilingual reliability.
GDPR, PIPL, and client-mandated data controls often eliminate models before performance even enters discussion.
Check jurisdictional requirements before evaluating feature lists.
No tool works perfectly out of the box. All four models need prompt engineering and review workflows to avoid hallucinations. The best implementations combine AI speed with human oversight at critical checkpoints.
Key Takeaways
| Key Point | What It Means | Action Item |
|---|---|---|
| Claude Opus 4.6 leads on Western legal reasoning | Highest LegalBench and BAR scores for US, UK, EU law | Choose for complex common-law document review and M&A due diligence |
| GLM-5 dominates Chinese-language legal tasks | Best CEPS score and native regulatory knowledge for China and ASEAN | Choose for Mandarin contracts, PRC compliance, and local court preparation |
| Gemini 3.1 Pro offers unmatched scale and flexibility | 2M token window and strongest multilingual legal performance | Choose for global firms with cross-border deals and diverse language needs |
| Wenxin 5.0 is the budget workhorse for China | Lowest cost with solid local performance, integrated with Baidu legal tools | Choose for high-volume Chinese domestic work with tight cost constraints |