• We evaluated NVIDIA’s new open-weight Nemotron 3 Ultra across our benchmark suite. It ranks #5 among open-weight models on the Vals Index, with a score of 43.99%.

• The model is strongest on domain-specific benchmarks. Among open-weight models, it ranks #3 on TaxEval v2 (73.10%), #4 on CorpFin v2 (65.46%), #5 on Finance Agent v2 (37.53%), and #6 on MedCode (38.62%).

• General reasoning is solid: Nemotron 3 Ultra scores 86.11% on GPQA Diamond, 85.76% on MMLU Pro, and 82.07% on LegalBench, landing between #5 and #7 among open-weight models on each.

• On coding, it scores 85.98% on LiveCodeBench, ranking #3 among open-weight models, and 50.94% on Terminal Bench 2.1, ranking #4 among open-weight models.

The model is text-only, with a 1M-token context window and 128k max output tokens. We ran it via the NVIDIA API with top_p set to 0.95.

• We evaluated Alibaba’s new Qwen 3.7 Plus on the Vals Index, where it ranks #13 with a score of 52.33%.

• Its strongest Index component was Vibe Code Bench, where it ranks #8 on the Index subset with a score of 46.94%. On the full Vibe Code Bench leaderboard, the model scores 46.39%.

• On coding benchmarks, Qwen 3.7 Plus matches Qwen 3.7 Max on the SWE-bench Verified Index subset at 66.67%, and scores 52.81% on Terminal Bench 2.1.

• On finance benchmarks, it scores 62.01% on CorpFin v2 and 41.25% on Finance Agent v2, trailing Qwen 3.7 Max while slightly improving on Qwen 3.6 Plus in Finance Agent v2.

The model was run via the Alibaba API at temperature 0.7, with preserve_thinking enabled, a 1M-token context window, and 65,536 max output tokens.

• MiniMax just released their latest open-weights MiniMax-M3 model, with multimodal support. It ranks #6 on the Vals Index (58.94%) and #6 on the Vals Multimodal Index (59.97%), making it the top open-weights model on both.

• It is also the top open-weights performer across multiple domain-specific benchmarks, including LegalBench, MedCode, and Finance Agent v2, where it scored 48.27% — a 20-point improvement from its predecessor, MiniMax-M2.7.

• On coding, we see a big improvement on Vibe Code Bench, where the model scores 47.57%, a massive 35-point increase from MiniMax-M2.7. On SWE-bench Verified (75.00%) and Terminal Bench 2.1 (53.56%), performance was mixed, ranking #17 and #12 respectively.

The model was run via the official MiniMax API at temperature 1, top_p 0.95, and 512k max output tokens.

Congrats to the MiniMax team on a strong release!

• We evaluated Anthropic’s new Claude Opus 4.8 across our benchmark suite. It is the new #1 model on the Vals Index (70.17%) and the Vals Multimodal Index (70.71%), edging out GPT 5.5 on both.

• Agentic work is the headline. The model is #1 on SWE-bench Verified (88.60%), #1 on Vibe Code Bench (82.72%), and #1 on ProofBench (69.00%). It also places #2 on Terminal Bench 2 (70.04%) and #2 on Finance Agent v2 (53.92%).

• Knowledge benchmarks land near the top: LCB 87.82% (#3), GPQA 92.42% (#4), MMLU Pro 89.58% (#4), and MMMU 86.59% (#9).

• Domain-specific benchmarks hold up: MortgageTax 69.91% (#2), MedCode 53.22% (#5), MedScribe 85.75% (#6), TaxEval v2 75.63% (#7), and CorpFin v2 66.71% (#8). Claude Opus 4.8 also picks up #3 on Sage (54.79%).

• The model still lags behind the field on LegalBench, where it ranks #27 at 83.57%.

The model has a 1M-token context window. Evaluations were run with compute effort set to “max”, a temperature of 1.0, and max output tokens set to 128k.

Congrats to the Anthropic team on the release!