Google (29 models) vs Meta (Llama) (14 models) - compared across composite scores, pricing, capabilities, and context windows.
| Capability | Meta (Llama) | Leader | |
|---|---|---|---|
Vision | 25/29 | 4/14 | |
Reasoning | 17/29 | 0/14 | |
Function Calling | 19/29 | 5/14 | |
JSON Mode | 26/29 | 7/14 | |
Web Search | 16/29 | 0/14 | |
Streaming | 27/29 | 14/14 | |
Image Output | 4/29 | 0/14 |
| Metric | Meta (Llama) | |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.040 Gemma 3 4B | $0.020 Llama Guard 3 8B |
| Cheapest Output (per 1M tokens) | $0.080 | $0.030 |
| Most Expensive Input (per 1M tokens) | $2.00 Gemini 3.1 Pro Preview Custom Tools | $0.510 Llama 3 70B Instruct |
| Most Expensive Output (per 1M tokens) | $12.00 | $0.740 |
| Free Models | 4 | 2 |
| Max Context Window | 1.0M | 1.0M |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Gemini 3 Flash Preview | 88 | $0.500 | $3.00 |
| Gemini 2.5 Pro | 84 | $1.25 | $10.00 |
| Gemini 2.5 Pro Preview 06-05 | 84 | $1.25 | $10.00 |
| Gemini 2.5 Pro Preview 05-06 | 84 | $1.25 | $10.00 |
| Gemini 3.1 Pro Preview Custom Tools | 81 | $2.00 | $12.00 |
| Gemini 3.1 Pro Preview | 81 | $2.00 | $12.00 |
| Gemma 4 31B (free) | 81 | Free | Free |
| Gemma 4 31B | 81 | $0.130 | $0.380 |
| Gemini 3.1 Flash Lite Preview | 80 | $0.250 | $1.50 |
| Gemini 2.5 Flash Lite Preview 09-2025 | 79 | $0.100 | $0.400 |
| Gemini 2.5 Flash Lite | 79 | $0.100 | $0.400 |
| Gemini 2.5 Flash | 79 | $0.300 | $2.50 |
| Gemma 2 27B | 77 | $0.650 | $0.650 |
| Gemma 4 26B A4B (free) | 73 | Free | Free |
| Gemma 4 26B A4B | 73 | $0.060 | $0.330 |
| Gemini 2.0 Flash | 72 | $0.100 | $0.400 |
| Gemini 2.0 Flash Lite | 59 | $0.075 | $0.300 |
| Lyria 3 Pro Preview | 40 | Free | Free |
| Lyria 3 Clip Preview | 40 | Free | Free |
| Gemma 3n 4B | 40 | $0.060 | $0.120 |
| 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 |
Compare any two AI providers side-by-side.
Google's portfolio strategy prioritizes coverage over excellence, with 27 vision-capable models versus Meta's 4, and 16 models supporting function calling versus Meta's 7. This breadth-first approach explains their 9 free models compared to Meta's 2, though their top performer (Gemini 2.5 Flash Lite Preview at 60/100) only edges out Llama 4 Maverick (54/100) by 6 points.
Meta's open source commitment eliminates licensing overhead, allowing them to match Google's lowest price point ($0.040/M) while capping at $0.740/M versus Google's $12.00/M ceiling. This 16x price ceiling difference reflects Meta's focus on commodity inference rather than premium enterprise features, though they sacrifice advanced capabilities with 0/14 models supporting reasoning versus Google's 16/34.
Google's 27 vision models provide redundancy and specialization options that Meta's 4 cannot match, particularly important when Google's vision models span the full $0.040-$12.00/M price range. However, Meta's vision models cluster in the $0.180-$0.740/M range with fully open weights, making them superior for on-premise deployments despite the 23-model disadvantage.
Google's 16 reasoning models and Meta's 0 reflect different architectural priorities - Google integrates search through separate APIs rather than model capabilities, while Meta's open source focus precludes proprietary web access. This explains why Google commands up to $12.00/M for advanced models while Meta caps at $0.740/M, targeting offline inference workloads.
Google's 9 free models span multiple capability sets including vision and function calling, while Meta's 2 free models represent just 14% of their portfolio versus Google's 26%. This disparity matters less than expected since Meta's 100% open source availability enables unlimited local usage, whereas Google's free tier models like Gemini variants still impose usage quotas.
Google wins decisively with 16 models supporting both vision and function calling out of their 34 total, while Meta offers just 4 vision models with only partial function calling overlap across their 14-model lineup. The $0.040 entry point is identical, but Google's Gemini 2.5 Flash Lite Preview combines both capabilities at competitive pricing, while Meta users must orchestrate multiple specialized models.