Framework & Model Comparisons

Interactive comparison tables for agentic AI frameworks, models, and benchmarks.

Agent Frameworks

Framework	Type	Language	Multi-Agent	State Mgmt	Best For
LangGraph	Graph-based	Python	Yes	Built-in	Complex workflows
CrewAI	Role-based	Python	Yes	Automatic	Team collaboration
AutoGen	Conversational	Python	Yes	Manual	Research, prototyping
LangChain	Chain-based	Python/JS	Limited	Manual	Simple agents
Semantic Kernel	Plugin-based	C#/Python	Yes	Built-in	Enterprise
Haystack	Pipeline	Python	Limited	Manual	RAG applications

Feature Comparison

Feature	LangGraph	CrewAI	AutoGen	LangChain
Visual debugging	Yes	Limited	No	Limited
Checkpointing	Yes	No	No	No
Human-in-the-loop	Yes	Yes	Yes	Manual
Streaming	Yes	Yes	Yes	Yes
Memory persistence	Yes	Limited	Manual	Manual
Tool integration	Excellent	Good	Good	Excellent
Learning curve	Medium	Low	Medium	Low
Documentation	Excellent	Good	Good	Excellent

LLM Providers

Provider	Models	Strengths	Weaknesses	Pricing
OpenAI	GPT-4o, GPT-4o-mini	Function calling, reliability	Cost at scale	$$$
Anthropic	Claude 3.5 Sonnet, Haiku	Long context, safety	Smaller ecosystem	$$$
Google	Gemini Pro, Flash	Multimodal, speed	Less agent-focused	$$
Mistral	Mistral Large, Small	Open weights, EU	Smaller context	$$
Meta	Llama 3.1 70B, 8B	Open source, local	Requires hosting	Free
Cohere	Command R+	RAG optimization	Limited tools	$$

Model Capabilities

Model	Context	Tool Use	Code	Reasoning	Speed
GPT-4o	128K	Excellent	Excellent	Excellent	Fast
GPT-4o-mini	128K	Good	Good	Good	Very Fast
Claude 3.5 Sonnet	200K	Excellent	Excellent	Excellent	Fast
Claude 3.5 Haiku	200K	Good	Good	Good	Very Fast
Gemini 1.5 Pro	1M	Good	Good	Good	Medium
Llama 3.1 70B	128K	Limited	Good	Good	Varies

RAG Strategies

Strategy	Retrieval	Generation	Best For	Complexity
Naive RAG	Vector search	Single pass	Simple QA	Low
Self-RAG	Adaptive	With reflection	Complex queries	Medium
CRAG	Corrective	With verification	Accuracy-critical	Medium
RAPTOR	Hierarchical	Multi-level	Long documents	High
GraphRAG	Graph-based	Community-aware	Multi-hop reasoning	High
HippoRAG	Memory-inspired	Contextual	Personalization	High

Benchmarks

Benchmark	Domain	Tasks	Metrics	Difficulty
AgentBench	General	8 envs	Success rate	Medium-Hard
WebArena	Web	812 tasks	Task completion	Hard
SWE-bench	Coding	2294 issues	Pass@k	Very Hard
GAIA	General	466 tasks	Accuracy	Hard
OSWorld	Desktop	369 tasks	Success rate	Hard
ToolBench	Tools	16K APIs	Win rate	Medium

Benchmark Results (Selected Models)

Model	AgentBench	WebArena	SWE-bench	GAIA
GPT-4o	4.01	14.9%	33.2%	53.7%
Claude 3.5 Sonnet	3.89	12.4%	49.0%	45.2%
Gemini 1.5 Pro	3.52	10.2%	28.1%	41.0%
Llama 3.1 70B	2.84	6.1%	22.7%	32.4%

Note: Scores vary by evaluation date and methodology. Check official leaderboards for current results.

Prompting Strategies

Strategy	Accuracy Boost	Token Cost	Best For
Zero-shot	Baseline	1x	Simple tasks
Few-shot	+5-15%	2-3x	Pattern matching
Chain-of-Thought	+10-25%	2-4x	Reasoning
Self-Consistency	+5-10%	5-10x	High-stakes
Tree-of-Thoughts	+15-30%	10-50x	Complex planning
ReAct	Variable	3-10x	Tool use

Tool Integration

Tool Type	Examples	Complexity	Security Risk
Read-only	Search, weather, calculator	Low	Low
State-modifying	File write, database update	Medium	Medium
External API	Email, Slack, payments	High	High
Code execution	Python, bash	High	Very High
Browser	Web scraping, form filling	High	High

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Last updated: December 2024. Data subject to change as models and frameworks evolve.