What fallback model performs best for short, multilingual answers?

[Isaac24Karat]

I'm currently refining the fallback strategy in an agentic RAG system and experimenting with different lightweight LLMs to handle short, multilingual responses — especially for queries where the primary agent fails or returns uncertain/confused output.

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🧪 Models I’ve Tested So Far:

• Claude Instant — generally good tone, but may over-explain
• Phi-3 Mini — excellent for compact English answers, but sometimes loses nuance in other languages
• Gemini Nano — decent balance, but hallucination rate spikes on named entities

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💬 What I'm Looking For:

• Strong performance in Hebrew, French, and German
• Brief answers with high factual precision
• Consistent formatting (for downstream formatting/parsing)

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❓Questions for You:

• Which fallback models have worked best in your multilingual RAG pipelines?
• Have you seen improvements by priming the fallback agent differently (e.g., role prompt vs zero-shot)?
• Any luck combining models (e.g., one for translation, one for summarization)?

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📎 This is part of a broader goal to build a resilient, modular RAG system that feels reliable in real-world deployments.

Happy to hear what others have tested and tuned!

[Isaac24Karat]

Quick update based on initial testing:

• Claude Instant: Still the most consistent across languages, especially French and German — though it tends to "pad" short answers with extra context.
• Phi-3 Mini: Surprisingly compact in English and Hebrew. Works well when paired with a strict role prompt like “Respond in 1 sentence.”
• Gemini Nano: Still unstable with named entities and mixed-language queries (like Hebrew/English), but very fast.

Next I'm planning to test:

• OpenRouter’s Dolphin 2.5 — reportedly concise
• Using a verifier agent after fallback to filter hallucinations

If anyone has tried using translation as a pre-step (e.g., always translate to English → answer → translate back), would love to hear how that went.

Thanks for the insights so far — happy to share more test results if helpful!

[Isaac24Karat]

Quick update based on more structured testing:

• Claude 3 Opus is currently my strongest fallback for short multilingual replies — particularly in Hebrew and French. It delivers context-aware answers and respects brevity when instructed to answer in 2–3 sentences.
• Mixtral performs well in general but tends to struggle with token-level consistency in Hebrew.
• I've now introduced a confidence score threshold system: if the primary model scores <0.7, the fallback agent is automatically triggered. Claude is the preferred reroute.

Next I’ll be testing:

• A verifier agent after Claude to double-check names/dates
• Whisper → Claude fallback path for voice-based inputs

Let me know if you've found better fallback behavior with other compact models!