Meta (Llama) (14 models) vs Amazon (5 models) - compared across composite scores, pricing, capabilities, and context windows.
| Meta (Llama) | Score | vs | Amazon | Score |
|---|---|---|---|---|
| Llama 4 Maverick | 67 | Nova 2 Lite | 61 | |
| Llama 3.3 70B Instruct | 67 | Nova Premier 1.0 | 40 | |
| Llama 3.3 70B Instruct (free) | 66 | Nova Lite 1.0 | 40 | |
| Llama 3.1 70B Instruct | 65 | Nova Micro 1.0 | 40 | |
| Llama 3 70B Instruct | 57 | Nova Pro 1.0 | 40 |
| Capability | Meta (Llama) | Amazon | Leader |
|---|---|---|---|
Vision | 4/14 | 4/5 | Tie |
Reasoning | 0/14 | 1/5 | Amazon |
Function Calling | 5/14 | 5/5 | Tie |
JSON Mode | 7/14 | 0/5 | Meta (Llama) |
Web Search | 0/14 | 0/5 | Tie |
Streaming | 14/14 | 5/5 | Meta (Llama) |
Image Output | 0/14 | 0/5 | Tie |
| Metric | Meta (Llama) | Amazon |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.020 Llama Guard 3 8B | $0.035 Nova Micro 1.0 |
| Cheapest Output (per 1M tokens) | $0.030 | $0.140 |
| Most Expensive Input (per 1M tokens) | $0.510 Llama 3 70B Instruct | $2.50 Nova Premier 1.0 |
| Most Expensive Output (per 1M tokens) | $0.740 | $12.50 |
| Free Models | 2 | 0 |
| Max Context Window | 1.0M | 1.0M |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Llama 4 Maverick | 67 | $0.150 | $0.600 |
| Llama 3.3 70B Instruct | 67 | $0.100 | $0.320 |
| Llama 3.3 70B Instruct (free) | 66 | Free | Free |
| Llama 3.1 70B Instruct | 65 | $0.400 | $0.400 |
| Llama 3 70B Instruct | 57 | $0.510 | $0.740 |
| Llama 4 Scout | 54 | $0.080 | $0.300 |
| Llama 3.1 8B Instruct | 44 | $0.020 | $0.050 |
| Llama Guard 4 12B | 40 | $0.180 | $0.180 |
| Llama Guard 3 8B | 40 | $0.480 | $0.030 |
| Llama 3.2 11B Vision Instruct | 40 | $0.245 | $0.245 |
| Llama 3 8B Instruct | 34 | $0.040 | $0.040 |
| Llama 3.2 3B Instruct (free) | 33 | Free | Free |
| Llama 3.2 3B Instruct | 33 | $0.051 | $0.340 |
| Llama 3.2 1B Instruct | 18 | $0.027 | $0.200 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Nova 2 Lite | 61 | $0.300 | $2.50 |
| Nova Premier 1.0 | 40 | $2.50 | $12.50 |
| Nova Lite 1.0 | 40 | $0.060 | $0.240 |
| Nova Micro 1.0 | 40 | $0.035 | $0.140 |
| Nova Pro 1.0 | 40 | $0.800 | $3.20 |
Compare any two AI providers side-by-side.
Meta prioritizes ecosystem building through volume and accessibility, with 2 free models and prices starting at $0.040/M tokens. Amazon's strategy targets enterprise customers willing to pay premium prices ($0.140-$12.50/M) for higher average quality, with their Nova 2 Lite matching Meta's best Llama 4 Maverick at 54/100.
Meta's open source approach enables ultra-low pricing for basic tasks, while Amazon's top-tier pricing reflects specialized enterprise features like their 1/5 reasoning capability that Meta completely lacks across all 14 models. The $0.740/M ceiling on Meta's most expensive model suggests they're targeting a fundamentally different market segment than Amazon's premium offerings.
Amazon's enterprise focus demands consistent API integration capabilities across their entire 5-model lineup, justifying their higher base price of $0.140/M. Meta's fragmented coverage reflects their community-driven development where only newer models like Llama 4 Maverick get advanced features, leaving 7 models without this critical capability.
While both achieve roughly 28-29% vision coverage across their portfolios, Amazon's smaller lineup means 80% of their models support vision versus Meta's scattered approach. Amazon's Nova 2 Lite combines vision with their top 54/100 performance and reasoning capabilities, while Meta's vision models average lower scores despite offering 2 free options.
Meta excels for startups and researchers needing free experimentation (2 models at $0), self-hosting flexibility, and rock-bottom inference costs starting at $0.040/M tokens. Amazon suits enterprises requiring consistent function calling (100% coverage), reasoning capabilities (20% vs Meta's 0%), and support guarantees that justify paying 3.5x more minimum ($0.140/M vs $0.040/M).