Skip to content

OpenAI vs Meta (Llama)

OpenAI (97 models) vs Meta (Llama) (8 models) - compared across composite scores, pricing, capabilities, and context windows.

Models
97
Avg Score
75
Top Model
Score: 93
Price Range
$0.130 - $600.00
per 1M output tokens
1 free4 open source1.1M max context

Meta (Llama)

View all models
Models
8
Avg Score
49
Top Model
Score: 68
Price Range
$0.080 - $0.800
per 1M output tokens
8 open source1.3M max context

Capability Comparison

CapabilityOpenAIMeta (Llama)Leader
Vision
78/973/8OpenAI
Reasoning
67/970/8OpenAI
Function Calling
89/975/8OpenAI
JSON Mode
95/977/8OpenAI
Web Search
76/970/8OpenAI
Streaming
95/978/8OpenAI
Image Output
4/970/8OpenAI

Pricing Comparison

MetricOpenAIMeta (Llama)
Cheapest Input (per 1M tokens)$0.025
gpt-oss-20b
$0.027
Llama 3.1 8B Instruct
Cheapest Output (per 1M tokens)$0.130$0.080
Most Expensive Input (per 1M tokens)$150.00
o1-pro
$0.400
Llama 4 Maverick
Most Expensive Output (per 1M tokens)$600.00$0.800
Free Models10
Max Context Window1.1M1.3M

All OpenAI Models (97)

ModelScoreInput $/MOutput $/M
GPT-5.5 Pro93$30.00$180.00
GPT-5.5 Pro (batch)93$15.00$90.00
GPT-5.593$5.00$30.00
GPT-5.5 (batch)93$2.50$15.00
GPT-5.4 Pro92$30.00$180.00
GPT-5.4 Pro (batch)92$15.00$90.00
GPT-5.492$2.50$15.00
GPT-5.4 (batch)92$1.25$7.50
GPT-5.3 Chat91$1.75$14.00
GPT-5.3-Codex91$1.75$14.00
GPT-5.2-Codex91$1.75$14.00
GPT-5.2 Chat91$1.75$14.00
GPT-5.2 Pro91$21.00$168.00
GPT-5.2 Pro (batch)91$10.50$84.00
GPT-5.291$1.75$14.00
GPT-5.2 (batch)91$0.875$7.00
GPT-5.6 Luna Pro89$0.100$0.600
GPT-5.6 Luna Pro (batch)89$0.100$0.600
GPT-5.6 Luna89$0.100$0.600
GPT-5.6 Luna (batch)89$0.100$0.600

All Meta (Llama) Models (8)

ModelScoreInput $/MOutput $/M
Llama 4 Maverick68$0.200$0.800
Llama 3.3 70B Instruct67$0.100$0.320
Llama 3.1 70B Instruct65$0.400$0.400
Llama 4 Scout55$0.100$0.300
Llama 3.1 8B Instruct45$0.050$0.080
Llama Guard 4 12B40$0.180$0.180
Llama 3.2 3B Instruct34$0.050$0.330
Llama 3.2 1B Instruct18$0.027$0.201
Frequently Asked Questions

OpenAI's portfolio strategy emphasizes specialized variants and legacy support, with 57 of 64 models supporting function calling versus Meta's 7 of 14. This breadth comes at a cost: OpenAI's average score of 49/100 barely exceeds Meta's 34/100 despite having 4.5x more models, suggesting diminishing returns from model proliferation.

OpenAI offers vision in 65.6% of its models compared to Meta's 28.6%, but Meta's Llama 4 Maverick (54/100) trails GPT-5.4 (67/100) by only 13 points without vision support. For pure text workloads, Meta's focused approach delivers 80% of OpenAI's performance at prices starting from $0.040/M tokens versus OpenAI's $0.110/M minimum.

OpenAI's $600/M ceiling reflects enterprise reasoning models with 34 of 64 models supporting reasoning capabilities, while Meta caps at $0.740/M with zero reasoning support across all 14 models. The sweet spot for cost-conscious deployments is Meta's $0.040/M tier, undercutting OpenAI's cheapest option by 63.6%.

OpenAI's value emerges in production scenarios requiring web search (31/64 models vs Meta's 0/14) or complex function calling where OpenAI's 89% model coverage dwarfs Meta's 50%. For self-hosted deployments or custom fine-tuning, Meta's complete open source portfolio and comparable 1.0M token context window make OpenAI's 5 open models irrelevant.

Both providers gate their best models behind paywalls: OpenAI's free tier likely excludes GPT-5.4 (67/100 score) while Meta's excludes Llama 4 Maverick (54/100 score). With Meta's entire lineup being open source, developers can self-host any model for free, making OpenAI's free tier useful primarily for testing their proprietary features like web search and advanced reasoning.

OpenAI vs Meta (Llama) - AI Provider Comparison (2026) | LM Market Cap