business_productivity
Best Model for RAG Q&A With Citations
Find the best model for grounded Q&A with citations from internal knowledge bases.
Full Analysis Available
Benchmark methodology, patterns in the data, and deployment notes
Provisional leader
gemini-2.5-pro
Best current option from the available benchmark evidence, but not yet a strong winner claim.
external/google/gemini-2-5-pro
31.6%
Score
48.1%
Confidence
34
Evidence
$3.44
per 1M tokens
Ranked Models
30
Evidence Quality
83%
Evidence Points
34
Top Signal
FACTS Benchmark Suite: facts_grounding_score_pct
Benchmark Sources
35
Last Updated
16h ago
All Ranked Models
| Rank | Model | Score |
|---|---|---|
| 🥇 | gemini-2.5-pro Strong on FACTS Benchmark Suite facts_grounding_score_pct and BasedAGI KB Q&A Eval overall_score_pct | 31.6% |
| 🥈 | gpt-5-2025-08-07 Strong on BasedAGI KB Q&A Eval overall_score_pct and FACTS Benchmark Suite facts_grounding_score_pct | 30.4% |
| 🥉 | gemini-3-pro-preview Strong on BasedAGI KB Q&A Eval overall_score_pct and Vals Finance Agent overall_accuracy_pct | 27.0% |
| #4 | gemini-3.1-pro-preview Strong on Vals Finance Agent overall_accuracy_pct and FACTS Benchmark Suite facts_search_score_pct | 26.7% |
| #5 | claude-sonnet-4.6 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 26.2% |
| #6 | gpt-5-mini-2025-08-07 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 25.6% |
| #7 | Grok-4-0709 Strong on Vals Finance Agent overall_accuracy_pct and FACTS Benchmark Suite facts_grounding_score_pct | 23.9% |
| #8 | gemini-3-flash-preview Strong on Vals Finance Agent overall_accuracy_pct and FACTS Benchmark Suite average_score_pct | 22.3% |
| #9 | gemini-3.1-flash-lite-preview Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 21.0% |
| #10 | gpt-5.2-2025-12-11 Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vals Finance Agent overall_accuracy_pct | 20.8% |
| #11 | claude-sonnet-4 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Galileo Agent Leaderboard v2 Avg TSQ | 19.4% |
| #12 | gpt-4.1-20250414 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Vals CorpFin v2 overall_accuracy_pct | 18.7% |
| #13 | gpt-5.4-2026-03-05 Strong on Vals Finance Agent overall_accuracy_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 18.4% |
| #14 | gemini-2.5-flash Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 17.8% |
| #16 | claude-opus-4-5-20251101 Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 16.6% |
| #17 | grok-4-fast-reasoning Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 16.1% |
| #19 | gpt-5.1-2025-11-13 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 15.9% |
| #20 | grok-4-1-fast-reasoning Strong on Vals Finance Agent overall_accuracy_pct and Vals CorpFin v2 overall_accuracy_pct | 14.4% |
| #21 | o3-20250416 Strong on SciArena Leaderboard rating_elo and FACTS Benchmark Suite facts_search_score_pct | 13.8% |
| #23 | claude-opus-4-6-thinking Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 13.8% |
| #24 | claude-opus-4.7 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 13.8% |
| #25 | qwen-2.5-72b-instruct Strong on Open LLM Leaderboard MMLU-Pro mmlu_pro_accuracy_pct and Open LLM Leaderboard GPQA gpqa | 13.8% |
| #27 | kimi-k2.5-thinking Strong on Vals Finance Agent overall_accuracy_pct and Vals CorpFin v2 overall_accuracy_pct | 13.3% |
| #28 | phi-4 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Open LLM Leaderboard GPQA gpqa | 12.9% |
| #33 | grok-4-1-fast-non-reasoning Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 11.6% |
| #34 | grok-4.20-0309-reasoning Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 11.4% |
| #42 | claude-opus-4-1-20250805 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and FACTS Benchmark Suite facts_grounding_score_pct | 10.2% |
| #46 | gpt-4o-2024-08-06 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Vectara HHEM Leaderboard overall_answer_rate_pct | 9.4% |
| #48 | gemini-2.5-flash-lite Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Galileo Agent Leaderboard v2 Avg TSQ | 9.4% |
| #49 | o4-mini Strong on Vals CorpFin v2 overall_accuracy_pct and SciArena Leaderboard rating_elo | 9.3% |
Head-to-Head: #1 vs #2
#1
Top Pickgemini-2.5-pro
Strong on FACTS Benchmark Suite facts_grounding_score_pct and BasedAGI KB Q&A Eval overall_score_pct
Conf 48.1%
#2
gpt-5-2025-08-07
Strong on BasedAGI KB Q&A Eval overall_score_pct and FACTS Benchmark Suite facts_grounding_score_pct
Conf 40.1%
Related Lookups
Best LLM for Code Generation
Benchmark-backed ranking of models for generating correct, secure code from requirements.
Best LLM for Debugging
Find the top-ranked models for localizing bugs and proposing fixes with explanations.
Best LLM for Unit Test Generation
Ranked models for generating meaningful unit tests and edge cases from code.
Best LLM for Code Review
Compare models for automated PR review covering correctness, security, and maintainability.
Best LLM for Autonomous Coding
Benchmark-backed ranking of models for end-to-end autonomous software engineering and issue resolution.
Best LLM for Function Calling
Compare models for reliable tool use, function selection, and multi-step API orchestration.