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ProxMenux/AppImage/config/verified_ai_models.json
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{
"_description": "Verified AI models for ProxMenux notifications. Only models listed here will be shown to users. Models are tested to work with the chat/completions API format.",
"_updated": "2026-09-02",
"_verifier": "Refreshed by .github/workflows/verify-ai-models.yml (daily). The workflow runs .github/scripts/ai-models-verifier/verify.py against every provider whose API key is configured in repository Secrets, then applies the report via apply.py — which honours per-provider `_exclude` lists. `_exclude` is intentionally minimal: it only drops models that are technically incapable of generating a chat completion for a normal prompt (safety classifiers, agentic-only endpoints, meta-routers, wrong modalities). Everything else the verifier passes is surfaced — including language-specialised models (Arabic, Chinese, ...), reasoning models, legacy families and dated snapshots — so a user with a specific need can still pick the model that fits. Manually re-run from the Actions tab (any branch) when a new model needs to be picked up out of cycle.",
"groq": {
"models": [
"allam-2-7b",
"qwen/qwen3.8-27b",
"openai/gpt-oss-120b"
],
"recommended": "allam-2-7b",
"_exclude": [
"openai/gpt-oss-safeguard-*",
"groq/compound",
"groq/compound-*"
],
"_note": "`_exclude` covers models the verifier may technically pass but that do not produce a usable chat completion: openai/gpt-oss-safeguard-* is a safety classifier (returns a category, not free text); groq/compound* is an agentic system that expects multi-step tool use, not a plain prompt."
},
"gemini": {
"models": [
"gemini-2.5-flash-lite",
"gemini-3.1-flash-lite-preview",
"gemini-3.1-flash-lite",
"gemini-flash-lite-latest",
"gemini-3.5-flash-lite",
"gemini-2.5-flash",
"gemini-3.5-flash",
"gemini-3-flash-preview",
"gemma-4-26b-a4b-it"
],
"recommended": "gemini-2.5-flash-lite",
"_exclude": [
"gemini-embedding-*",
"gemini-*-pro*",
"gemini-*-thinking*"
],
"_deprecated": [
"gemini-2.0-flash",
"gemini-2.0-flash-lite",
"gemini-1.5-flash",
"gemini-1.0-pro",
"gemini-pro"
],
"_note": "`_exclude` drops embeddings (wrong modality) and Pro / thinking variants that reject `thinkingConfig.thinkingBudget: 0` and therefore never return a visible completion within a reasonable token budget — technical failure with our current provider config."
},
"openai": {
"models": [
"gpt-4.1-nano-2025-04-14",
"gpt-4.1-nano",
"gpt-4.1-2025-04-14",
"gpt-4.1",
"gpt-4o-2024-05-13",
"gpt-4o-2024-11-20",
"gpt-5-nano",
"gpt-5-nano-2025-08-07",
"gpt-3.5-turbo-1106",
"gpt-3.5-turbo-0125",
"gpt-4o-mini-2024-07-18",
"gpt-4.1-mini-2025-04-14",
"gpt-4o-mini",
"gpt-3.5-turbo-16k",
"gpt-4.1-mini",
"gpt-3.5-turbo",
"gpt-4o",
"gpt-4",
"gpt-4-0613",
"gpt-4-turbo",
"gpt-4-turbo-2024-04-09",
"gpt-4o-2024-08-06"
],
"recommended": "gpt-4.1-nano",
"_exclude": [
"gpt-4o-audio*",
"gpt-4o-realtime*",
"gpt-4o-search*",
"gpt-4o-transcribe*",
"gpt-4o-mini-audio*",
"gpt-4o-mini-realtime*",
"gpt-4o-mini-search*",
"gpt-4o-mini-transcribe*",
"gpt-4o-mini-tts",
"computer-use-*"
],
"_note": "`_exclude` covers wrong-modality variants (audio, realtime, search, transcribe, tts) that cannot handle a plain notification-translation prompt, plus computer-use which requires an agent loop. All other OpenAI chat/completion models are surfaced — including legacy families (gpt-3.5, gpt-4), reasoning models (o-series, gpt-5.x non-chat) and dated snapshots — so users can pick by their own criteria (cost, quality, reproducibility). openai_provider.py already handles reasoning models via max_completion_tokens + reasoning_effort=minimal."
},
"anthropic": {
"models": [
"claude-haiku-4-5-20251001",
"claude-opus-4-8",
"claude-opus-4-5-20251101",
"claude-opus-4-7",
"claude-fable-5",
"claude-sonnet-4-5-20250929",
"claude-fable-5-1",
"claude-opus-4-6",
"claude-sonnet-4-6"
],
"recommended": "claude-haiku-4-5-20251001",
"_exclude": [],
"_note": "No technical exclusions — every Claude generation returns free-text completions for a plain prompt. The verifier tests each model listed under `models`; if a specific ID stops working upstream it simply drops out of the passing set. Anthropic does not expose a public models-list API, so new models must be added to `models` manually before the verifier can test them."
},
"openrouter": {
"models": [
"minimax/minimax-m3:free",
"poolside/laguna-s-2.1:free"
],
"recommended": "minimax/minimax-m3:free",
"_exclude": [
"openrouter/*",
"*/*-audio*",
"*/*-audio-*",
"*/*-tts*",
"*/*-whisper*",
"*/*-embed*",
"*/*-embedding*",
"*/*-image*",
"*/*-vision-only*"
],
"_note": "OpenRouter aggregates hundreds of models; the free-tier variants (:free suffix) are intentionally supported per user request and never blocked. `_exclude` covers only meta-routers (`openrouter/free`, `openrouter/auto` — they route dynamically to something else, so their behaviour is not the model the user picked) and wrong-modality models (audio, tts, whisper, embeddings, image, vision-only). Everything else — chat models across every family, language and price tier — is surfaced so the user can pick the fit."
},
"ollama": {
"_note": "Ollama models are local, we don't filter them. User manages their own models.",
"models": [],
"recommended": ""
}
}