Meta (Llama) (14 models) vs xAI (Grok) (11 models) - compared across composite scores, pricing, capabilities, and context windows.
| Capability | Meta (Llama) | xAI (Grok) | Leader |
|---|---|---|---|
Vision | 4/14 | 6/11 | xAI (Grok) |
Reasoning | 0/14 | 9/11 | xAI (Grok) |
Function Calling | 5/14 | 10/11 | xAI (Grok) |
JSON Mode | 7/14 | 11/11 | xAI (Grok) |
Web Search | 0/14 | 11/11 | xAI (Grok) |
Streaming | 14/14 | 11/11 | Meta (Llama) |
Image Output | 0/14 | 0/11 | Tie |
| Metric | Meta (Llama) | xAI (Grok) |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.020 Llama Guard 3 8B | $0.200 Grok 4.1 Fast |
| Cheapest Output (per 1M tokens) | $0.030 | $0.500 |
| Most Expensive Input (per 1M tokens) | $0.510 Llama 3 70B Instruct | $3.00 Grok 4 |
| Most Expensive Output (per 1M tokens) | $0.740 | $15.00 |
| Free Models | 2 | 0 |
| Max Context Window | 1.0M | 2.0M |
| 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 |
|---|---|---|---|
| Grok 4.20 | 89 | $1.25 | $2.50 |
| Grok 4 | 88 | $3.00 | $15.00 |
| Grok 4.20 Multi-Agent | 88 | $2.00 | $6.00 |
| Grok 4.1 Fast | 78 | $0.200 | $0.500 |
| Grok 4.3 | 76 | $1.25 | $2.50 |
| Grok 3 | 74 | $3.00 | $15.00 |
| Grok 3 Beta | 74 | $3.00 | $15.00 |
| Grok 4 Fast | 73 | $0.200 | $0.500 |
| Grok 3 Mini Beta | 63 | $0.300 | $0.500 |
| Grok 3 Mini | 51 | $0.300 | $0.500 |
| Grok Code Fast 1 | 40 | $0.200 | $1.50 |
Compare any two AI providers side-by-side.
xAI focuses on premium performance with all 10 models supporting function calling (9/10) and web search (10/10), compared to Meta's 7/14 and 0/14 respectively. This capability-first approach explains why Grok 4.1 Fast hits 75/100 while Llama 4 Maverick peaks at 54/100, though it means abandoning the budget segment entirely.
Despite having 14 open-source models versus xAI's 0, Meta lags significantly in reasoning (0/14 models) and web search (0/14), while xAI delivers reasoning in 8/10 models and web search across all 10. The open-source advantage doesn't translate to capability leadership, with Meta's 1.0M max context falling short of xAI's 2.0M.
Meta provides vision in 4/14 models starting from budget tiers, while xAI offers it in 5/10 models but exclusively at premium prices ($0.500+/M minimum). For cost-sensitive vision tasks, Meta's lower-performing but affordable options make sense; for production applications where the 75/100 vs 54/100 quality gap matters, xAI's premium vision models justify their 12.5x higher starting price.
xAI's strategy targets enterprise deployments where every model includes premium features like web search (10/10) and near-universal function calling (9/10), justifying prices from $0.500-$15.00/M tokens. Meta's free tier and $0.040/M entry point reflect its developer ecosystem focus, trading off advanced capabilities for accessibility across its 14-model lineup.
Meta distributes its 14 models across performance tiers to serve different budgets, resulting in a 34/100 portfolio average but maximum flexibility. xAI maintains quality consistency with its 10-model lineup never dropping below mid-tier performance, evident in 8/10 models supporting reasoning versus Meta's 0/14, though this philosophy eliminates budget options entirely.