customer_experience
Best LLM for Multilingual Support
Ranked models for handling multilingual support conversations with cultural awareness and clarity.
Provisional leader
anthropic/claude-sonnet-4
Best current option from the available benchmark evidence, but not yet a strong winner claim.
external/anthropic/claude-sonnet-4
23.6%
Score
32.9%
Confidence
28
Evidence
$6.00
per 1M tokens
Ranked Models
30
Evidence Quality
83%
Evidence Points
28
Top Signal
LanguageBench: overall:mean
Benchmark Sources
48
Last Updated
10h ago
All Ranked Models
| Rank | Model | Score |
|---|---|---|
| 🥇 | claude-sonnet-4 Strong on LanguageBench overall:mean and LanguageBench Translation Official (Split) translation_to:bleu | 23.6% |
| 🥈 | gemini-2.5-flash Strong on LanguageBench overall:mean and FACTS Benchmark Suite facts_grounding_score_pct | 22.8% |
| 🥉 | gemini-2.5-pro Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 20.9% |
| #4 | gemini-3.1-pro-preview Strong on Vals Finance Agent overall_accuracy_pct and FACTS Benchmark Suite facts_search_score_pct | 19.6% |
| #5 | gpt-4.1-20250414 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Galileo Agent Leaderboard v2 Avg AC | 19.6% |
| #6 | gpt-5-2025-08-07 Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vals Finance Agent overall_accuracy_pct | 18.7% |
| #7 | gpt-5-mini-2025-08-07 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 18.7% |
| #9 | gemini-3-flash-preview Strong on Vals Finance Agent overall_accuracy_pct and Vectara HHEM Leaderboard overall_answer_rate_pct | 16.4% |
| #10 | Llama-3.1-70B-Instruct Strong on LanguageBench overall:mean and Open LLM Leaderboard IFEval ifeval | 15.4% |
| #12 | Llama-3.3-70B-Instruct Strong on LanguageBench overall:mean and Open LLM Leaderboard IFEval ifeval | 15.3% |
| #13 | claude-sonnet-4.6 Strong on Vals Finance Agent overall_accuracy_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 15.3% |
| #14 | Grok-4-0709 Strong on Vals Finance Agent overall_accuracy_pct and FACTS Benchmark Suite facts_grounding_score_pct | 15.2% |
| #15 | gpt-5.2-2025-12-11 Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vals Finance Agent overall_accuracy_pct | 15.1% |
| #16 | gemini-3.1-flash-lite-preview Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 15.1% |
| #17 | phi-4 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and LanguageBench overall:mean | 15.0% |
| #18 | gemini-3-pro-preview Strong on Vals Finance Agent overall_accuracy_pct and Vectara HHEM Leaderboard overall_answer_rate_pct | 14.2% |
| #20 | qwen-2.5-72b-instruct Strong on Open LLM Leaderboard IFEval ifeval and Open LLM Leaderboard MMLU-Pro mmlu_pro_accuracy_pct | 13.2% |
| #21 | gpt-5.4-2026-03-05 Strong on Vectara HHEM Leaderboard overall_hallucination_error_pct and Vals Finance Agent overall_accuracy_pct | 13.1% |
| #27 | claude-opus-4-5-20251101 Strong on FACTS Benchmark Suite facts_grounding_score_pct and Vectara HHEM Leaderboard overall_hallucination_error_pct | 12.0% |
| #28 | grok-4-fast-reasoning Strong on Vectara HHEM Leaderboard overall_answer_rate_pct and Vals Finance Agent overall_accuracy_pct | 12.0% |
| #35 | gpt-5.1-2025-11-13 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 11.5% |
| #39 | gpt-4.1-mini-20250414 Strong on OpenVLM MTVQA Official mtvqa_score_pct and Galileo Agent Leaderboard v2 Avg AC | 11.1% |
| #45 | Qwen3-Embedding-0.6B Strong on MTEB STS & Summarization Proxy Official sts_score_pct and MTEB Retrieval and Rerank (Official) retrieval_score_pct | 10.7% |
| #47 | grok-4-1-fast-reasoning Strong on Vals Finance Agent overall_accuracy_pct and Vectara HHEM Leaderboard overall_answer_rate_pct | 10.6% |
| #49 | o3-20250416 Strong on SciArena Leaderboard rating_elo and FACTS Benchmark Suite facts_search_score_pct | 10.4% |
| #72 | claude-opus-4-6-thinking Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 9.7% |
| #74 | claude-opus-4.7 Strong on Vals Finance Agent overall_accuracy_pct and Vals Finance Agent complex_retrieval_accuracy_pct | 9.6% |
| #101 | kimi-k2.5-thinking Strong on Vals Finance Agent overall_accuracy_pct and Vals CorpFin v2 overall_accuracy_pct | 8.8% |
| #105 | gpt-4o Strong on CRMArena Function Calling overall_score_pct and OpenVLM MTVQA Official mtvqa_score_pct | 8.7% |
| #108 | MaziyarPanahi/calme-3.2-instruct-78b Strong on Open LLM Leaderboard MMLU-Pro mmlu_pro_accuracy_pct and Open LLM Leaderboard GPQA gpqa | 8.6% |
Head-to-Head: #1 vs #2
#1
Top Pickanthropic/claude-sonnet-4
Strong on LanguageBench overall:mean and LanguageBench Translation Official (Split) translation_to:bleu
Conf 32.9%
#2
gemini-2.5-flash
Strong on LanguageBench overall:mean and FACTS Benchmark Suite facts_grounding_score_pct
Conf 31.3%
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.