mirror of
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refactor: reorganize providers and update model configurations
- Rename DeepInfraChat to DeepInfra across all files - Move DeepInfra from needs_auth to main Provider directory - Rename LMArenaBeta to LMArena throughout codebase - Move search-related providers to new search subdirectory (GoogleSearch, SearXNG, YouTube) - Move deprecated providers to not_working directory (Free2GPT, LegacyLMArena, PenguinAI, ImageLabs, har) - Add new Mintlify provider with custom AI assistant implementation - Update Anthropic provider with Claude 4 models and Opus 4.1 parameter handling - Update Grok provider with Grok 4 models and improved streaming support - Update GithubCopilot with expanded model list including o3-mini, o4-mini, gpt-5 previews - Update LambdaChat default model from deepseek-r1 to deepseek-llama3.3-70b - Update TeachAnything default model from gemini-1.5-pro to gemma - Remove DeepInfra from needs_auth directory - Update all model_map references from DeepInfraChat to DeepInfra - Update all model_map references from LMArenaBeta to LMArena - Add beta_headers support to Anthropic for special features - Improve Mintlify provider with system prompt handling and streaming - Update model configurations in models.py to reflect provider changes
This commit is contained in:
kqlio67
parent
2cf62a8e63
commit
9bac34fc88
26 changed files with 641 additions and 517 deletions
120
g4f/models.py
120
g4f/models.py
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@ -10,14 +10,13 @@ from .Provider import (
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Chatai,
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Cloudflare,
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Copilot,
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DeepInfraChat,
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Free2GPT,
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DeepInfra,
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HuggingSpace,
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Grok,
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DeepseekAI_JanusPro7b,
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ImageLabs,
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Kimi,
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LambdaChat,
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Mintlify,
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OIVSCodeSer2,
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OIVSCodeSer0501,
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OperaAria,
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@ -42,7 +41,7 @@ from .Provider import (
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HuggingFace,
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HuggingFaceMedia,
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HuggingFaceAPI,
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LMArenaBeta,
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LMArena,
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Groq,
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MetaAI,
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MicrosoftDesigner,
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@ -157,15 +156,16 @@ default = Model(
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OIVSCodeSer2,
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Blackbox,
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Copilot,
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DeepInfraChat,
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DeepInfra,
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OperaAria,
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Startnest,
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LambdaChat,
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PollinationsAI,
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Together,
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Free2GPT,
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Chatai,
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WeWordle,
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Mintlify,
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TeachAnything,
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OpenaiChat,
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Cloudflare,
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])
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@ -176,7 +176,7 @@ default_vision = VisionModel(
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base_provider = "",
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best_provider = IterListProvider([
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Blackbox,
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DeepInfraChat,
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DeepInfra,
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OIVSCodeSer0501,
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OIVSCodeSer2,
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PollinationsAI,
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@ -292,7 +292,7 @@ gpt_oss_120b = Model(
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name = 'gpt-oss-120b',
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long_name = 'openai/gpt-oss-120b',
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base_provider = 'OpenAI',
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best_provider = IterListProvider([Together, DeepInfraChat, HuggingFace, OpenRouter, Groq])
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best_provider = IterListProvider([Together, DeepInfra, HuggingFace, OpenRouter, Groq])
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)
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# dall-e
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@ -345,7 +345,7 @@ llama_3_70b = Model(
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llama_3_1_8b = Model(
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name = "llama-3.1-8b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DeepInfraChat, Together, Cloudflare])
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best_provider = IterListProvider([DeepInfra, Together, Cloudflare])
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)
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llama_3_1_70b = Model(
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@ -382,27 +382,27 @@ llama_3_2_11b = VisionModel(
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llama_3_2_90b = Model(
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name = "llama-3.2-90b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DeepInfraChat, Together])
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best_provider = IterListProvider([DeepInfra, Together])
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)
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# llama-3.3
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llama_3_3_70b = Model(
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name = "llama-3.3-70b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, Together, HuggingChat, HuggingFace])
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best_provider = IterListProvider([DeepInfra, LambdaChat, Together, HuggingChat, HuggingFace])
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)
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# llama-4
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llama_4_scout = Model(
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name = "llama-4-scout",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI, Together, Cloudflare])
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best_provider = IterListProvider([DeepInfra, PollinationsAI, Together, Cloudflare])
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)
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llama_4_maverick = Model(
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name = "llama-4-maverick",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, Together])
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best_provider = IterListProvider([DeepInfra, Together])
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)
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### MistralAI ###
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@ -433,7 +433,7 @@ mistral_small_24b = Model(
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mistral_small_3_1_24b = Model(
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name = "mistral-small-3.1-24b",
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base_provider = "Mistral AI",
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best_provider = IterListProvider([DeepInfraChat, PollinationsAI])
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best_provider = IterListProvider([DeepInfra, PollinationsAI])
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)
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### NousResearch ###
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@ -455,32 +455,32 @@ phi_3_5_mini = Model(
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phi_4 = Model(
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name = "phi-4",
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base_provider = "Microsoft",
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best_provider = IterListProvider([DeepInfraChat, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, HuggingSpace])
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)
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phi_4_multimodal = VisionModel(
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name = "phi-4-multimodal",
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base_provider = "Microsoft",
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best_provider = IterListProvider([DeepInfraChat, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, HuggingSpace])
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)
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phi_4_reasoning_plus = Model(
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name = "phi-4-reasoning-plus",
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base_provider = "Microsoft",
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# wizardlm
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wizardlm_2_7b = Model(
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name = 'wizardlm-2-7b',
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base_provider = 'Microsoft',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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wizardlm_2_8x22b = Model(
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name = 'wizardlm-2-8x22b',
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base_provider = 'Microsoft',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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### Google DeepMind ###
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@ -491,19 +491,6 @@ gemini = Model(
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best_provider = Gemini
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)
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# gemini-1.5
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gemini_1_5_flash = Model(
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name = 'gemini-1.5-flash',
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base_provider = 'Google',
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best_provider = IterListProvider([Free2GPT, TeachAnything])
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)
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gemini_1_5_pro = Model(
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name = 'gemini-1.5-pro',
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base_provider = 'Google',
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best_provider = IterListProvider([Free2GPT, TeachAnything])
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)
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# gemini-2.0
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gemini_2_0_flash = Model(
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name = 'gemini-2.0-flash',
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@ -540,7 +527,7 @@ gemini_2_5_pro = Model(
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codegemma_7b = Model(
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name = 'codegemma-7b',
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base_provider = 'Google',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# gemma
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@ -554,14 +541,14 @@ gemma_2b = Model(
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gemma_1_1_7b = Model(
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name = 'gemma-1.1-7b',
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base_provider = 'Google',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# gemma-2
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gemma_2_9b = Model(
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name = 'gemma-2-9b',
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base_provider = 'Google',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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gemma_2_27b = Model(
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@ -574,19 +561,19 @@ gemma_2_27b = Model(
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gemma_3_4b = Model(
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name = 'gemma-3-4b',
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base_provider = 'Google',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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gemma_3_12b = Model(
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name = 'gemma-3-12b',
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base_provider = 'Google',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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gemma_3_27b = Model(
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name = 'gemma-3-27b',
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base_provider = 'Google',
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best_provider = IterListProvider([DeepInfraChat, Together])
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best_provider = IterListProvider([DeepInfra, Together])
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)
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gemma_3n_e4b = Model(
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@ -676,7 +663,7 @@ qwen_2_5_72b = Model(
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qwen_2_5_coder_32b = Model(
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name = 'qwen-2.5-coder-32b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([PollinationsAI, LambdaChat, Together, HuggingChat])
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best_provider = IterListProvider([PollinationsAI, Together, HuggingChat])
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)
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qwen_2_5_1m = Model(
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@ -701,25 +688,25 @@ qwen_2_5_vl_72b = Model(
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qwen_3_235b = Model(
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name = 'qwen-3-235b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([DeepInfraChat, Together, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, Together, HuggingSpace])
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)
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qwen_3_32b = Model(
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name = 'qwen-3-32b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, Together, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, LambdaChat, Together, HuggingSpace])
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)
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qwen_3_30b = Model(
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name = 'qwen-3-30b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([DeepInfraChat, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, HuggingSpace])
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)
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qwen_3_14b = Model(
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name = 'qwen-3-14b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([DeepInfraChat, HuggingSpace])
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best_provider = IterListProvider([DeepInfra, HuggingSpace])
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)
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qwen_3_4b = Model(
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@ -744,7 +731,7 @@ qwen_3_0_6b = Model(
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qwq_32b = Model(
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name = 'qwq-32b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([DeepInfraChat, Together, HuggingChat])
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best_provider = IterListProvider([DeepInfra, Together, HuggingChat])
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)
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### DeepSeek ###
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@ -752,26 +739,26 @@ qwq_32b = Model(
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deepseek_v3 = Model(
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name = 'deepseek-v3',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat, Together])
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best_provider = IterListProvider([DeepInfra, Together])
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)
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# deepseek-r1
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deepseek_r1 = Model(
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name = 'deepseek-r1',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI, Together, HuggingChat, HuggingFace])
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best_provider = IterListProvider([DeepInfra, PollinationsAI, Together, HuggingChat, HuggingFace])
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)
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deepseek_r1_turbo = Model(
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name = 'deepseek-r1-turbo',
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base_provider = 'DeepSeek',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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deepseek_r1_distill_llama_70b = Model(
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name = 'deepseek-r1-distill-llama-70b',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat, Together])
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best_provider = IterListProvider([DeepInfra, Together])
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)
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deepseek_r1_distill_qwen_1_5b = Model(
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@ -789,46 +776,46 @@ deepseek_r1_distill_qwen_14b = Model(
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deepseek_r1_distill_qwen_32b = Model(
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name = 'deepseek-r1-distill-qwen-32b',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat])
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best_provider = IterListProvider([DeepInfra])
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)
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# deepseek-v2
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deepseek_prover_v2 = Model(
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name = 'deepseek-prover-v2',
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base_provider = 'DeepSeek',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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deepseek_prover_v2_671b = Model(
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name = 'deepseek-prover-v2-671b',
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base_provider = 'DeepSeek',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# deepseek-v3-0324
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deepseek_v3_0324 = Model(
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name = 'deepseek-v3-0324',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat, LambdaChat])
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best_provider = DeepInfra
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)
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deepseek_v3_0324_turbo = Model(
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name = 'deepseek-v3-0324-turbo',
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base_provider = 'DeepSeek',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# deepseek-r1-0528
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deepseek_r1_0528 = Model(
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name = 'deepseek-r1-0528',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI])
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best_provider = IterListProvider([DeepInfra, PollinationsAI])
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)
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deepseek_r1_0528_turbo = Model(
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name = 'deepseek-r1-0528-turbo',
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base_provider = 'DeepSeek',
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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# janus
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@ -860,7 +847,7 @@ grok_3_r1 = Model(
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kimi = Model(
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name = 'kimi-k2',
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base_provider = 'kimi.com',
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best_provider = IterListProvider([Kimi, HuggingFace, DeepInfraChat, Groq]),
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best_provider = IterListProvider([Kimi, HuggingFace, DeepInfra, Groq]),
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long_name = "moonshotai/Kimi-K2-Instruct"
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)
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@ -899,7 +886,7 @@ r1_1776 = Model(
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nemotron_70b = Model(
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name = 'nemotron-70b',
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base_provider = 'Nvidia',
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best_provider = IterListProvider([LambdaChat, Together, HuggingChat, HuggingFace])
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best_provider = IterListProvider([Together, HuggingChat, HuggingFace])
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)
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### Cognitive Computations ###
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@ -907,34 +894,27 @@ nemotron_70b = Model(
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dolphin_2_6 = Model(
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name = "dolphin-2.6",
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base_provider = "Cognitive Computations",
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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dolphin_2_9 = Model(
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name = "dolphin-2.9",
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base_provider = "Cognitive Computations",
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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### DeepInfra ###
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airoboros_70b = Model(
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name = "airoboros-70b",
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base_provider = "DeepInfra",
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best_provider = DeepInfraChat
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best_provider = DeepInfra
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)
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### Lizpreciatior ###
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lzlv_70b = Model(
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name = "lzlv-70b",
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base_provider = "Lizpreciatior",
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best_provider = DeepInfraChat
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)
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### Liquid AI ###
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lfm_40b = Model(
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name = "lfm-40b",
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base_provider = "Liquid AI",
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best_provider = LambdaChat
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best_provider = DeepInfra
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)
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### Opera ###
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@ -955,7 +935,7 @@ evil = Model(
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sdxl_turbo = ImageModel(
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name = 'sdxl-turbo',
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base_provider = 'Stability AI',
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best_provider = IterListProvider([HuggingFaceMedia, PollinationsImage, ImageLabs])
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best_provider = IterListProvider([HuggingFaceMedia, PollinationsImage])
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)
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sd_3_5_large = ImageModel(
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@ -1010,7 +990,7 @@ flux_canny = ImageModel(
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flux_kontext_max = ImageModel(
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name = 'flux-kontext',
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base_provider = 'Black Forest Labs',
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best_provider = IterListProvider([PollinationsAI, Azure, LMArenaBeta, Together])
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best_provider = IterListProvider([PollinationsAI, Azure, LMArena, Together])
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)
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flux_dev_lora = ImageModel(
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