Model Leaderboard
Top AI models ranked by benchmark · manually updated
| Model | Tier | Contextunfold_more | SWE-benchunfold_more | MMLUarrow_downward | Input $/1Munfold_more | Output $/1M |
|---|---|---|---|---|---|---|
Llama 4 MaverickMeta | balanced | 1000K | - | 85.5% | OSS | OSS |
Claude Fable 5Anthropic | flagship | 1000K | 80.3% | - | $10.00 | $50.00 |
Claude Opus 4.8Anthropic | flagship | 1000K | 88.6% | - | $5.00 | $25.00 |
GPT-5.5OpenAI | flagship | 1049K | - | - | $5.00 | $30.00 |
Gemini 3.1 ProGoogle | flagship | 1000K | 80.6% | - | $2.00 | $12.00 |
Grok 4.3xAI | flagship | 1000K | 74.9% | - | $1.25 | $2.50 |
DeepSeek V4 ProDeepSeek | flagship | 1000K | 80.6% | - | $1.74 | $3.48 |
Gemini 2.5 Pro Deep ThinkGoogle | reasoning | 1000K | - | - | $3.50 | $10.50 |
Claude Sonnet 4.6Anthropic | balanced | 200K | - | - | $3.00 | $15.00 |
Qwen 3.5 235BAlibaba | balanced | 262K | - | - | OSS | OSS |
Claude Haiku 4.5Anthropic | fast | 200K | - | - | $0.80 | $4.00 |
Gemini 2.5 FlashGoogle | fast | 1000K | - | - | $0.15 | $0.60 |
DeepSeek V4 FlashDeepSeek | fast | 1000K | - | - | $0.28 | $0.42 |
Llama 4 ScoutMeta | fast | 10000K | - | - | OSS | OSS |
SWE-bench = real GitHub coding tasks (higher = better). MMLU = general knowledge. Prices from provider APIs. OSS models: self-host or use via API providers. Last updated Jun 2026.
Tools Directory
Frameworks, platforms, and infra for GenAI development
Most popular framework for building LLM-powered applications, chains, and agents.
Data framework for LLM applications — RAG, structured extraction, and query pipelines.
TypeScript toolkit for building AI-powered UIs with streaming, tool use, and multi-modal support.
Production-ready NLP framework for building custom pipelines with RAG, search, and agents.
Microsoft's SDK for integrating LLMs into C#, Python, and Java enterprise applications.
Framework for orchestrating role-playing, autonomous AI agents working as a team.
Microsoft's framework for building multi-agent applications where agents converse to solve tasks.
Build stateful, multi-actor agent applications as controllable graphs with cycles and branches.
Visual platform for building and operating AI applications with drag-and-drop workflows.
Drag-and-drop UI for building LLM flows and AI agents with LangChain components.
Workflow automation platform with native AI nodes for building agentic workflows without code.
Run LLMs locally with a simple CLI. Supports Llama, Mistral, Gemma, Phi and hundreds more.
Desktop app to discover, download, and run local LLMs with a ChatGPT-like UI.
High-throughput, memory-efficient inference engine for LLMs. The standard for production self-hosting.
Anthropic's open standard for connecting AI assistants to data sources and tools.
Hosted platform for building AI assistants with persistent threads, code interpreter, and file search.
ML experiment tracking, model versioning, and dataset management for the full ML lifecycle.
Observability and testing platform for LLM applications built with LangChain.
Open-source LLM engineering platform for tracing, evaluation, and prompt management.
Managed vector database built for production AI applications with low latency at scale.
Open-source embedding database for AI applications. Simple API, runs embedded or as a server.
High-performance vector search engine with rich filtering, payload indexing, and Rust core.
Open-source vector database with built-in ML model integrations and GraphQL API.
AI Vendor Map
34 vendors · 6 categories · Updated June 2026
Foundation Models
(8)Claude Fable 5, Opus 4.8, Sonnet 4.6. Leader in safety-focused frontier AI. API + AWS/GCP.
GPT-5.5, o-series reasoning. Most widely adopted API. Microsoft integration.
Gemini 3.1 Pro, 2.5 Flash. 1M context, native multimodal, Vertex AI. Strongest on benchmarks Jun 2026.
Open weights. Scout (10M context), Maverick (MoE). Self-host or via API providers.
MIT-licensed MoE. $1.74/$3.48 per 1M — near-frontier quality at fraction of cost.
European frontier AI. Mistral Large 2, Codestral. Strong multilingual + code. GDPR-friendly.
Grok 4.3: $1.25/$2.50 per 1M, 1M context, native video. Great price/performance ratio.
Command R+ for enterprise RAG. Embed v3 for best-in-class embeddings. Strong enterprise focus.
Cloud Platforms
(6)Managed access to Anthropic, Meta, Mistral, Cohere. Guardrails, Agents, Knowledge Bases built-in.
OpenAI + 1,700+ models from HuggingFace. Deep enterprise integration, RBAC, compliance.
Gemini + OSS models. Agent Builder, Grounding, RAG Engine. Best for Gemini-heavy workloads.
Fastest OSS inference (Llama, Qwen, Mixtral). 200+ models, competitive pricing.
Run any OSS model via API. Pay-per-prediction. Great for image, audio, and niche models.
Edge inference across 300 PoPs. Low latency, zero cold starts. OSS models at edge.
Frameworks
(5)Most popular LLM framework. Chains, agents, RAG. Python + TypeScript. 95k GitHub stars.
Data framework for RAG. Best for complex document ingestion and retrieval pipelines.
TypeScript-first AI for web. Streaming, tool use, multi-provider. Best for Next.js.
Production-ready pipelines. Deepset-backed. Strong for search and enterprise RAG.
Stanford project — compiles prompts into optimized programs. Best for systematic prompt optimization.
Agentic / Auto
(6)Multi-agent orchestration with role-based agents. 30k stars. Best for collaborative agent teams.
Graph-based agentic workflows from LangChain. Supports cycles, conditional branches, state.
Microsoft multi-agent framework. AutoGen Studio for no-code agent building.
Autonomous AI agent that completes complex tasks end-to-end. Browser, code, files.
Workflow automation with 400+ integrations + AI nodes. Self-hostable. Strong EU adoption.
LLM app development platform. Drag-and-drop agent builder, RAG, workflow. 60k stars.
MLOps / Observ.
(4)Experiment tracking, model registry, LLM monitoring. De facto standard for ML teams.
LLM observability from LangChain. Trace, evaluate, and optimize LLM applications.
Open-source LLM observability. Traces, evals, prompt management. Self-hostable.
ML + LLM monitoring. Drift detection, explainability, A/B testing for AI models.
Vector DBs
(5)Managed vector DB. Fastest time-to-production. Serverless tier for small workloads.
Open-source vector DB with hybrid search. GraphQL API, multi-tenancy, on-prem option.
Simplest OSS vector DB. Zero config for local dev. Perfect for prototyping.
Rust-based, high-performance. Payload filtering, named vectors, cloud + self-host.
PostgreSQL extension for vector similarity search. Zero new infra for Postgres shops.
AI Architecture Patterns
7 patterns · When to use each · Common pitfalls · June 2026
Basic Prompt Engineering
LowSimple Q&A, text transformation, classification, summarization. No external data needed. Fastest to ship.
RAG (Retrieval-Augmented Generation)
MediumQ&A over company documents, knowledge bases, or any proprietary content. Prevents hallucination on factual queries.
Tool Use / Function Calling
MediumLLM needs to interact with external systems: search the web, query a database, call an API, execute code.
Agentic Loop (ReAct)
HighMulti-step tasks where the next action depends on previous results. The LLM acts as a planner and executor.
Multi-Agent System
HighParallel subtasks, specialization, or peer-review between agents. Scale beyond single-agent context limits.
Fine-tuned Model
HighConsistent domain-specific behavior at scale. Style, format, or domain knowledge the base model lacks. High-volume inference where prompt size matters for cost.
Guardrails & Safety Layer
MediumAny production deployment. Add input/output validation to prevent prompt injection, PII leakage, and off-topic responses.