Llama
Meta's open-weight family, and the reason local models took off.
Llama is Meta's open-weight family and the one that made running a serious model on your own hardware normal — most local tooling was built for it first, so support is everywhere. The Llama 4 models are mixture-of-experts and multimodal, with very large context windows, and the line includes Llama Guard, a classifier for filtering input and output rather than a chat model. Meta's newer work ships under a different name, so check the dates on this family before choosing it.
At a glance — Llama Guard 4 12B
- Cost
- $0.18 in · $0.18 out per 1M tokensBudget
- Memory
- 164K tokens — about 250 pages
- Reads
- Text · Images
- Can do
- Use tools (agents) (not supported)
- Structured output (not supported)
- Thinking mode (not supported)
- Reliability
- 100.00% uptime, last 24h
- Released
- Apr 30, 2025
Advanced details
- API model ID
meta-llama/llama-guard-4-12b- Max output
- 16K tokens
- Knowledge cutoff
- 2024-08-31
- Tokenizer
- Other
Providers
The same model, hosted by different companies. OpenRouter picks one per request and falls back to the next if it fails.
| Provider | Input /1M | Output /1M | Cached /1M | Max output | Uptime 24h |
|---|---|---|---|---|---|
| DeepInfra · bf16 | $0.18 | $0.18 | — | 16K | 100.00% |
Supported parameters
- frequency_penalty
- logit_bias
- max_tokens
- min_p
- presence_penalty
- repetition_penalty
- seed
- stop
- temperature
- top_k
- top_p
Live from OpenRouter, refreshed hourly.
Key info
- Pricing
- Open source
- Category
- Models
- Best for
- Intermediate
- Made by
- Meta
- Weights
- Open
- Good for
- Local setups, where tooling support is widest