Benchmark · April 2026

Meta AI vs ChatGPT vs Gemini vs Claude

This is an early independent comparison designed to help teams think more clearly about model choice. It is not exhaustive. Fields are labeled to distinguish what we've directly observed, what we've estimated from public sources, and what reflects editorial interpretation. We're publishing it early because honest, incomplete information is more useful than polished information that hides its assumptions.

This is an early comparison surface, not a lab-grade ranking. Our goal is to make model tradeoffs easier to reason about, not to declare a universal winner.

This is an early benchmark. Some fields are editorial assessments or estimates from publicly available information, not controlled measurements. Hover over labels for evidence notes.

Model behavior changes with each release. Outputs vary by prompt, context, and access tier. Full methodology is explained on the Methodology page. Use this as one input — not a definitive answer.

measured — directly observed or testedestimated — inferred from public dataeditorial — manual assessment or review

Meta AI

ChatGPT (GPT-4o)

OpenAI

Best forBroad instruction-following, coding, general-purpose assistants, plugin/tool use

WeaknessesOutput consistency varies across runs; pricing increases with context length

estimatedFreshness

Web browsing available; training cutoff ~early 2024 without browsing

estimatedSpeed

Moderate-to-fast; higher latency on complex completions

measuredCost

$0 (free tier) to $20/mo consumer; API from ~$5/M tokens

NotesLargest ecosystem; widest third-party tool integration at time of writing.

Updated: April 2026

Gemini (1.5 Pro)

Google

Best forMultimodal tasks, long-context documents, Google Workspace integration

WeaknessesInconsistent performance on reasoning-heavy tasks in independent testing

editorialFreshness

Real-time grounding via Google Search; strong recency handling

estimatedSpeed

Variable; 1.5 Flash considerably faster than Pro at lower quality

measuredCost

$0 (free tier); Gemini Advanced ~$20/mo; API pricing tiered by model

NotesBest-in-class for very long documents and multimodal inputs.

Updated: April 2026

Claude (3.5 Sonnet)

Anthropic

Best forLong-context reasoning, nuanced writing, code review, structured outputs

WeaknessesMore cautious refusals on edge cases; slower than GPT-4o Flash variants

estimatedFreshness

No real-time browsing by default; knowledge cutoff ~early 2024

estimatedSpeed

Moderate; Haiku variant significantly faster for lower-complexity tasks

measuredCost

$0 (Claude.ai free); Pro ~$20/mo; API from ~$3/M input tokens

NotesPreferred by many developers for code and document-heavy workflows.

Updated: April 2026

Model	Provider	Best for	Weaknesses	Freshness	Speed	Cost band	Notes	Updated
Meta AI	Meta	Conversational tasks, social-context Q&A, consumer-facing applications	Less established for complex multi-step reasoning or professional code review	editorial Real-time search integration available; knowledge cutoff varies by access method	editorial Fast for consumer tier; API latency unverified at this stage	editorial Free tier via Meta products; API pricing not yet widely published	Rapidly developing. Public benchmarks limited relative to competitors.	April 2026
ChatGPT (GPT-4o)	OpenAI	Broad instruction-following, coding, general-purpose assistants, plugin/tool use	Output consistency varies across runs; pricing increases with context length	estimated Web browsing available; training cutoff ~early 2024 without browsing	estimated Moderate-to-fast; higher latency on complex completions	measured $0 (free tier) to $20/mo consumer; API from ~$5/M tokens	Largest ecosystem; widest third-party tool integration at time of writing.	April 2026
Gemini (1.5 Pro)	Google	Multimodal tasks, long-context documents, Google Workspace integration	Inconsistent performance on reasoning-heavy tasks in independent testing	editorial Real-time grounding via Google Search; strong recency handling	estimated Variable; 1.5 Flash considerably faster than Pro at lower quality	measured $0 (free tier); Gemini Advanced ~$20/mo; API pricing tiered by model	Best-in-class for very long documents and multimodal inputs.	April 2026
Claude (3.5 Sonnet)	Anthropic	Long-context reasoning, nuanced writing, code review, structured outputs	More cautious refusals on edge cases; slower than GPT-4o Flash variants	estimated No real-time browsing by default; knowledge cutoff ~early 2024	estimated Moderate; Haiku variant significantly faster for lower-complexity tasks	measured $0 (Claude.ai free); Pro ~$20/mo; API from ~$3/M input tokens	Preferred by many developers for code and document-heavy workflows.	April 2026

Summary

Plain-language observations

Where each model seems strongest

ΛChatGPT — widest general coverage; strongest ecosystem of integrations and plugins.
ΛClaude — long documents, nuanced reasoning, and code review workflows. Preferred by many developers.
ΛGemini — multimodal tasks and real-time information; deepest Google Workspace integration.
ΛMeta AI — consumer Q&A and social-context use cases; rapidly developing capabilities.

Where tradeoffs appear

ΛNo model leads clearly across all dimensions at this stage.
ΛSpeed and cost tradeoffs vary significantly within each provider's model family (e.g. Flash vs Pro, Haiku vs Sonnet).
ΛReal-time information access is uneven — and matters a great deal for some workflows.
ΛRefusal patterns and tone differ in ways that affect professional use cases.

Why model choice depends on workflow

A model that performs well in a general benchmark may underperform significantly in your specific context — the length of your inputs, the structure of your prompts, the tolerance for refusals, and the need for real-time information all affect which model fits best.

Multi-model approaches are increasingly common: different models for different tasks within the same product. This benchmark is a starting point for thinking through those decisions, not a ranking to follow blindly.

What this benchmark doesn't cover

Domain-specific performance (legal, medical, financial), fine-tuned variants, enterprise API reliability, and cost-at-scale are not assessed here. Those require structured evaluation specific to your workflow — which is part of what MetaAI.io is exploring.

Explore specific comparisons