
ai-models
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
- Installs
- 299
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/alinaqi/maggy --skill ai-models- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ai-models automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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)
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-4-6',
sonnet4: 'claude-sonnet-5',
// Fast & cheap - high volume tasks
haiku: 'claude-haiku-4-5-20251001',
} as const;
Usage
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-4-5-20251001 (Haiku 4.5)
├── Best for: Classification, extraction, high-volume
├── Context: 200K tokens
├── Cost: $1/$5 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)
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
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)
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
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)
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
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, emotional range
├── Latency: ~1s+ (not for real-time)
├── Languages: 74
└── Use when: Quality over speed, pre-rendered
eleven_turbo_v2_5
├── Best for: Balanced quality and speed
├── Latency: ~250-300ms
├── Languages: 32
└── Use when: Good quality with reasonable latency
eleven_flash_v2_5
├── Best for: Real-time, conversational AI
├── Latency: <75ms
├── Languages: 32
└── Use when: Live voice agents, chatbots
Replicate
Documentation
- API Docs: https://replicate.com/docs
- Models: https://replicate.com/explore
- Pricing: https://replicate.com/pricing
Popular Models (December 2025)
const REPLICATE_MODELS = {
// FLUX.2 (Latest - November 2025)
flux2Pro: 'black-forest-labs/flux-2-pro',
flux2Flex: 'black-forest-labs/flux-2-flex',
flux2Dev: 'black-forest-labs/flux-2-dev',
// FLUX.1 (Still excellent)
flux11Pro: 'black-forest-labs/flux-1.1-pro',
fluxKontext: 'black-forest-labs/flux-kontext', // Image editing
fluxSchnell: 'black-forest-labs/flux-schnell',
// Video
stableVideo4D: 'stability-ai/sv4d-2.0',
// Audio
musicgen: 'meta/musicgen',
// LLMs (if needed outside main providers)
llama: 'meta/llama-3.2-90b-vision',
} as const;
Usage
import Replicate from 'replicate';
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
// Image generation with FLUX.2
const output = await replicate.run('black-forest-labs/flux-2-pro', {
input: {
prompt: 'A serene mountain landscape at sunset',
aspect_ratio: '16:9',
output_format: 'webp',
},
});
// Image editing with Kontext
const edited = await replicate.run('black-forest-labs/flux-kontext', {
input: {
image: 'https://...',
prompt: 'Change the sky to sunset colors',
},
});
Model Selection
flux-2-pro
├── Best for: Highest quality, up to 4MP
├── Speed: ~6s
├── Cost: $0.015 + per megapixel
└── Use when: Professional quality needed
flux-2-flex
├── Best for: Fine details, typography
├── Speed: ~22s
├── Cost: $0.06 per megapixel
└── Use when: Need precise control
flux-2-dev (Open source)
├── Best for: Fast generation
├── Speed: ~2.5s
├── Cost: $0.012 per megapixel
└── Use when: Speed over quality
flux-kontext
├── Best for: Image editing with text
├── Speed: Variable
├── Cost: Per run
└── Use when: Edit existing images
Stability AI
Documentation
- API Docs: https://platform.stability.ai/docs/api-reference
- Models: https://stability.ai/stable-image
- Pricing: https://platform.stability.ai/pricing
Latest Models (December 2025)
const STABILITY_MODELS = {
// Image generation
sd35Large: 'sd3.5-large',
sd35LargeTurbo: 'sd3.5-large-turbo',
sd3Medium: 'sd3-medium',
// Video
sv4d: 'sv4d-2.0', // Stable Video 4D 2.0
// Upscaling
upscale: 'esrgan-v1-x2plus',
} as const;
Usage
const response = await fetch(
'https://api.stability.ai/v2beta/stable-image/generate/sd3',
{
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${process.env.STABILITY_API_KEY}`,
},
body: JSON.stringify({
prompt: 'A futuristic city at night',
output_format: 'webp',
aspect_ratio: '16:9',
model: 'sd3.5-large',
}),
}
);
Mistral AI
Documentation
- API Docs: https://docs.mistral.ai
- Models: https://docs.mistral.ai/getting-started/models
- Pricing: https://mistral.ai/technology/#pricing
Latest Models (December 2025)
const MISTRAL_MODELS = {
// Flagship
large: 'mistral-large-latest', // Points to 2411
// Medium tier
medium: 'mistral-medium-2505', // Medium 3
// Small/Fast
small: 'mistral-small-2506', // Small 3.2
// Code specialized
codestral: 'codestral-2508',
devstral: 'devstral-medium-2507',
// Reasoning (Magistral)
magistralMedium: 'magistral-medium-2507',
magistralSmall: 'magistral-small-2507',
// Audio
voxtral: 'voxtral-small-2507',
// OCR
ocr: 'mistral-ocr-2505',
} as const;
Usage
import MistralClient from '@mistralai/mistralai';
const client = new MistralClient(process.env.MISTRAL_API_KEY);
const response = await client.chat({
model: 'mistral-large-latest',
messages: [{ role: 'user', content: 'Hello!' }],
});
// Code completion with Codestral
const codeResponse = await client.chat({
model: 'codestral-2508',
messages: [{ role: 'user', content: 'Write a Python function to...' }],
});
Model Selection
mistral-large-latest (123B params)
├── Best for: Complex reasoning, knowledge tasks
├── Context: 128K tokens
└── Use when: Need high capability
codestral-2508
├── Best for: Code generation, 80+ languages
├── Speed: 2.5x faster than predecessor
└── Use when: Code-focused tasks
magistral-medium-2507
├── Best for: Multi-step reasoning
├── Specialty: Transparent chain-of-thought
└── Use when: Need reasoning traces
Voyage AI (Embeddings)
Documentation
- API Docs: https://docs.voyageai.com
- Models: https://docs.voyageai.com/docs/embeddings
- Pricing: https://www.voyageai.com/pricing
Latest Models (December 2025)
const VOYAGE_MODELS = {
// General purpose
large2: 'voyage-large-2',
large2Instruct: 'voyage-large-2-instruct',
// Code specialized
code2: 'voyage-code-2',
code3: 'voyage-code-3',
// Multilingual
multilingual2: 'voyage-multilingual-2',
// Domain specific
law2: 'voyage-law-2',
finance2: 'voyage-finance-2',
} as const;
Usage
const response = await fetch('https://api.voyageai.com/v1/embeddings', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${process.env.VOYAGE_API_KEY}`,
},
body: JSON.stringify({
model: 'voyage-code-3',
input: ['Your code to embed'],
}),
});
const { data } = await response.json();
const embedding = data[0].embedding;
Quick Reference
Cost Comparison (per 1M tokens, approx.)
| Provider | Cheap | Mid | Premium |
|---|---|---|---|
| Anthropic | $0.25 (Haiku) | $3 (Sonnet 4.5) | $5 (Opus 4.5) |
| OpenAI | $0.15 (4.1-nano) | $2 (4.1) | $15+ (o3) |
| $0.04 (Flash-lite) | $0.08 (Flash) | $1.25 (Pro) | |
| Mistral | $0.25 (Small) | $2.70 (Medium) | $8 (Large) |
Best For Each Task
Reasoning/Analysis → Claude Opus 4.5, o3, Gemini 3 Pro
Code Generation → Claude Sonnet 4.5, Codestral 2508, GPT-4.1
Fast Responses → Claude Haiku, GPT-4.1-mini, Gemini Flash
Long Context → Gemini 2.5 Pro (2M), GPT-4.1 (1M), Claude (200K)
Vision → GPT-4.1, Claude Sonnet, Gemini 3 Pro
Embeddings → Voyage code-3, text-embedding-3-small
Voice Synthesis → Eleven Labs v3/flash, OpenAI TTS
Image Generation → FLUX.2 Pro, DALL-E 3, SD 3.5
Video Generation → Stable Video 4D 2.0, Runway
Image Editing → FLUX Kontext, gpt-image-1
Environment Variables Template
# .env.example (NEVER commit actual keys)
# LLMs
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
GOOGLE_API_KEY=AI...
MISTRAL_API_KEY=...
# Media
ELEVENLABS_API_KEY=...
REPLICATE_API_TOKEN=r8_...
STABILITY_API_KEY=sk-...
# Embeddings
VOYAGE_API_KEY=pa-...
Model Update Checklist
When models update:
□ Check official changelog/blog
□ Update model ID strings
□ Test with existing prompts
□ Compare output quality
□ Check pricing changes
□ Update context limits if changed
Sources
FAQ
What does the ai-models skill do?
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
How do I install ai-models?
Run npx skills add https://github.com/alinaqi/maggy --skill ai-models in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ai-models/ (personal) or .claude/skills/ai-models/ (project).
Which AI agents can use ai-models?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ai-models safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ai-models?
It is published by alinaqi in alinaqi/maggy. It has 299 recorded installs.
More from alinaqi/maggy
pwa-development
alinaqi/maggy
Progressive Web Apps - service workers, caching strategies, offline, Workbox
playwright-testing
alinaqi/maggy
E2E testing with Playwright - Page Objects, cross-browser, CI/CD
android-kotlin
alinaqi/maggy
Android Kotlin development with Coroutines, Jetpack Compose, Hilt, and MockK testing
code-review
alinaqi/maggy
Mandatory code reviews via /code-review before commits and deploys
ui-mobile
alinaqi/maggy
Mobile UI patterns - React Native, iOS/Android, touch targets
posthog-analytics
alinaqi/maggy
PostHog analytics, event tracking, feature flags, dashboards
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available