We’ve released Legal Research Bench, a private benchmark that tests whether agents can handle realistic US legal research across eight practice areas. Each task uses case-law search, web search, and document retrieval to answer a question, graded against rubrics authored and peer-reviewed by practicing lawyers.

• Claude Opus 4.8 leads at 43.75% all-pass, followed by GPT 5.5 (40.39%) and Claude Sonnet 4.6 (38.46%).
• GLM 5.2 is the top open-weight model at 31.25%, ahead of MiniMax-M3 (29.81%).
• GLM 5.2 is the cost-efficiency leader at $0.89 per test, versus $2.82 for Claude Opus 4.8 and $7.40 for GPT 5.5.

We evaluated models on Harvey’s Legal Agent Benchmark, which tests an agent’s ability to complete legal work. Each task asks an agent to answer a client inquiry using shell and file-editing tools, plus skills for Word, Excel, and PowerPoint.

• Claude Fable 5 ranks #1 at 11.25% with Claude Opus 4.8 fallback, followed by Claude Opus 4.8 at 9.58% and Claude Sonnet 4.6 at 5.00%. Without fallback, Fable 5 still ranks #1 at 10.42%.
• MiniMax-M3 is the top open-weight model at 4.17%, ahead of GPT 5.5 at 3.75%.
• Claude Fable 5 ran at $19.23 per test, compared with $10.22 for Claude Opus 4.8, $3.04 for Claude Sonnet 4.6, and $1.46 for MiniMax-M3.

• z.AI just released their latest open-weights GLM 5.2 reasoning model. It’s the #1 open-weight model on the Vals Index (65.02%, #5 overall), reclaiming the top open-weight spot from MiniMax-M3 — a 12.5-point jump over its predecessor, GLM 5.1 (52.45%).

• It’s strongest on coding: #1 open-weight and #3 overall on SWE-bench Verified (82.80%), and #1 open-weight on both Terminal-Bench 2.1 (67.79%) and Vibe Code Bench (63.96%) — the latter a 32-point leap from GLM 5.1.

• It also leads open-weight models on agentic tasks, ranking #1 open-weight on Finance Agent v2 (49.70%) and #1 open-weight on Code Migration (37.87%).

• On the index it comes in at $2.08/test — pricier than MiniMax-M3 ($1.50) and GLM 5.1 ($0.86), but well below frontier closed models like Claude Fable 5 ($5.16).

Eval settings: temperature=1, top_p=0.95, up to 131k max output tokens, run via the native z.AI API. Context window: 1M tokens.

Congrats to the team at z.AI on the release!

We’ve released Code Migration, a proprietary benchmark that asks whether models can reimplement working programs in another language. Submissions are graded purely on behavior, the share of hidden tests the rebuilt program passes, across a CLI split (30 repositories migrated across Python, Java, Kotlin, Rust, and C++) and a COBOL-to-Java split.

• Claude Fable 5 leads CLI migration at 60.1%, well clear of Claude Opus 4.8 (40.1%) and GPT 5.5 (36.9%). Rebuilding command-line tools across five languages remains hard for the field.
• COBOL-to-Java is a much tighter race, with GPT 5.5 and Claude Opus 4.7 tied on top at 70.0% and several models close behind.
• GPT 5.5 is the cost-efficiency leader, reaching 45.2% overall at about $6 per task, roughly a fifth the cost of the comparably accurate Claude Opus 4.8 (47.2%) and the best accuracy-per-dollar at the frontier.