ai-models
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
What this skill does
# AI Models Reference Skill
**Last Updated: December 2025**
## Philosophy
**Use the right model for the job.** Bigger isn't always better - match model capabilities to task requirements. Consider cost, latency, and accuracy tradeoffs.
## Model Selection Matrix
| Task | Recommended | Why |
|------|-------------|-----|
| Complex reasoning | Claude Opus 4.5, o3, Gemini 3 Pro | Highest accuracy |
| Fast chat/completion | Claude Haiku, GPT-4.1 mini, Gemini Flash | Low latency, cheap |
| Code generation | Claude Sonnet 4.5, Codestral, GPT-4.1 | Strong coding |
| Vision/images | Claude Sonnet, GPT-4o, Gemini 3 Pro | Multimodal |
| Embeddings | text-embedding-3-small, Voyage | Cost-effective |
| Voice synthesis | Eleven Labs v3, OpenAI TTS | Natural sounding |
| Image generation | FLUX.2, DALL-E 3, SD 3.5 | Different styles |
---
## Anthropic (Claude)
### Documentation
- **API Docs**: https://docs.anthropic.com
- **Models Overview**: https://docs.anthropic.com/en/docs/about-claude/models/overview
- **Pricing**: https://www.anthropic.com/pricing
### Latest Models (December 2025)
```typescript
const CLAUDE_MODELS = {
// Flagship - highest capability
opus: 'claude-opus-4-5-20251101',
// Balanced - best for most tasks
sonnet: 'claude-sonnet-4-5-20250929',
// Previous generation (still excellent)
opus4: 'claude-opus-4-20250514',
sonnet4: 'claude-sonnet-4-20250514',
// Fast & cheap - high volume tasks
haiku: 'claude-haiku-3-5-20241022',
} as const;
```
### Usage
```typescript
import Anthropic from '@anthropic-ai/sdk';
const anthropic = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
});
const response = await anthropic.messages.create({
model: 'claude-sonnet-4-5-20250929',
max_tokens: 1024,
messages: [
{ role: 'user', content: 'Hello, Claude!' }
],
});
```
### Model Selection
```
claude-opus-4-5-20251101 (Opus 4.5)
├── Best for: Complex analysis, research, nuanced writing
├── Context: 200K tokens
├── Cost: $5/$25 per 1M tokens (input/output)
└── Use when: Accuracy matters most
claude-sonnet-4-5-20250929 (Sonnet 4.5)
├── Best for: Code, general tasks, balanced performance
├── Context: 200K tokens
├── Cost: $3/$15 per 1M tokens
└── Use when: Default choice for most applications
claude-haiku-3-5-20241022 (Haiku 3.5)
├── Best for: Classification, extraction, high-volume
├── Context: 200K tokens
├── Cost: $0.25/$1.25 per 1M tokens
└── Use when: Speed and cost matter most
```
---
## OpenAI
### Documentation
- **API Docs**: https://platform.openai.com/docs
- **Models**: https://platform.openai.com/docs/models
- **Pricing**: https://openai.com/pricing
### Latest Models (December 2025)
```typescript
const OPENAI_MODELS = {
// GPT-5 series (latest)
gpt5: 'gpt-5.2',
gpt5Mini: 'gpt-5-mini',
// GPT-4.1 series (recommended for most)
gpt41: 'gpt-4.1',
gpt41Mini: 'gpt-4.1-mini',
gpt41Nano: 'gpt-4.1-nano',
// Reasoning models (o-series)
o3: 'o3',
o3Pro: 'o3-pro',
o4Mini: 'o4-mini',
// Legacy but still useful
gpt4o: 'gpt-4o', // Still has audio support
gpt4oMini: 'gpt-4o-mini',
// Embeddings
embeddingSmall: 'text-embedding-3-small',
embeddingLarge: 'text-embedding-3-large',
// Image generation
dalle3: 'dall-e-3',
gptImage: 'gpt-image-1',
// Audio
tts: 'tts-1',
ttsHd: 'tts-1-hd',
whisper: 'whisper-1',
} as const;
```
### Usage
```typescript
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});
// Chat completion
const response = await openai.chat.completions.create({
model: 'gpt-4.1',
messages: [
{ role: 'user', content: 'Hello!' }
],
});
// With vision
const visionResponse = await openai.chat.completions.create({
model: 'gpt-4.1',
messages: [
{
role: 'user',
content: [
{ type: 'text', text: 'What is in this image?' },
{ type: 'image_url', image_url: { url: 'https://...' } },
],
},
],
});
// Embeddings
const embedding = await openai.embeddings.create({
model: 'text-embedding-3-small',
input: 'Your text here',
});
```
### Model Selection
```
o3 / o3-pro
├── Best for: Math, coding, complex multi-step reasoning
├── Context: 200K tokens
├── Cost: Premium pricing
└── Use when: Hardest problems, need chain-of-thought
gpt-4.1
├── Best for: General tasks, coding, instruction following
├── Context: 1M tokens (!)
├── Cost: Lower than GPT-4o
└── Use when: Default choice, replaces GPT-4o
gpt-4.1-mini / gpt-4.1-nano
├── Best for: High-volume, cost-sensitive
├── Context: 1M tokens
├── Cost: Very low
└── Use when: Simple tasks at scale
o4-mini
├── Best for: Fast reasoning at low cost
├── Context: 200K tokens
├── Cost: Budget reasoning
└── Use when: Need reasoning but cost-conscious
```
---
## Google (Gemini)
### Documentation
- **API Docs**: https://ai.google.dev/docs
- **Models**: https://ai.google.dev/gemini-api/docs/models/gemini
- **Pricing**: https://ai.google.dev/pricing
### Latest Models (December 2025)
```typescript
const GEMINI_MODELS = {
// Gemini 3 (Latest)
gemini3Pro: 'gemini-3-pro-preview',
gemini3ProImage: 'gemini-3-pro-image-preview',
gemini3Flash: 'gemini-3-flash-preview',
// Gemini 2.5 (Stable)
gemini25Pro: 'gemini-2.5-pro',
gemini25Flash: 'gemini-2.5-flash',
gemini25FlashLite: 'gemini-2.5-flash-lite',
// Specialized
gemini25FlashTTS: 'gemini-2.5-flash-preview-tts',
gemini25FlashAudio: 'gemini-2.5-flash-native-audio-preview-12-2025',
// Previous generation
gemini2Flash: 'gemini-2.0-flash',
} as const;
```
### Usage
```typescript
import { GoogleGenerativeAI } from '@google/generative-ai';
const genAI = new GoogleGenerativeAI(process.env.GOOGLE_API_KEY);
const model = genAI.getGenerativeModel({ model: 'gemini-2.5-flash' });
const result = await model.generateContent('Hello!');
const response = result.response.text();
// With vision
const visionModel = genAI.getGenerativeModel({ model: 'gemini-2.5-pro' });
const imagePart = {
inlineData: {
data: base64Image,
mimeType: 'image/jpeg',
},
};
const result = await visionModel.generateContent(['Describe this:', imagePart]);
```
### Model Selection
```
gemini-3-pro-preview
├── Best for: "Best model in the world for multimodal"
├── Context: 2M tokens
├── Cost: Premium
└── Use when: Need absolute best quality
gemini-2.5-pro
├── Best for: State-of-the-art thinking, complex tasks
├── Context: 2M tokens
├── Cost: $1.25/$5 per 1M tokens
└── Use when: Long context, complex reasoning
gemini-2.5-flash
├── Best for: Fast, balanced performance
├── Context: 1M tokens
├── Cost: $0.075/$0.30 per 1M tokens
└── Use when: Speed and cost matter
gemini-2.5-flash-lite
├── Best for: Ultra-fast, lowest cost
├── Context: 1M tokens
├── Cost: $0.04/$0.15 per 1M tokens
└── Use when: High volume, simple tasks
```
---
## Eleven Labs (Voice)
### Documentation
- **API Docs**: https://elevenlabs.io/docs
- **Models**: https://elevenlabs.io/docs/models
- **Pricing**: https://elevenlabs.io/pricing
### Latest Models (December 2025)
```typescript
const ELEVENLABS_MODELS = {
// Latest - highest quality (alpha)
v3: 'eleven_v3',
// Production ready
multilingualV2: 'eleven_multilingual_v2',
turboV2_5: 'eleven_turbo_v2_5',
// Ultra-low latency
flashV2_5: 'eleven_flash_v2_5',
flashV2: 'eleven_flash_v2', // English only
} as const;
```
### Usage
```typescript
import { ElevenLabsClient } from 'elevenlabs';
const elevenlabs = new ElevenLabsClient({
apiKey: process.env.ELEVENLABS_API_KEY,
});
// Text to speech
const audio = await elevenlabs.textToSpeech.convert('voice-id', {
text: 'Hello, world!',
model_id: 'eleven_turbo_v2_5',
voice_settings: {
stability: 0.5,
similarity_boost: 0.75,
},
});
// Stream audio (for real-time)
const audioStream = await elevenlabs.textToSpeech.convertAsStream('voice-id', {
text: 'Streaming audio...',
model_id: 'eleven_flash_v2_5',
});
```
### Model Selection
```
eleven_v3 (Alpha)
├── Best for: Highest quality, emoRelated in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.