StatusOperational Live status
LLMAPI discountUp to −25%
Models on LLMAPI7
From$0.06 / 1M blended
RegionsSelf-hosted
Best uptime (24h)100.00%
Verdict
Meta releases the Llama family of open-weight models, the de facto standard for teams that need to self-host, fine-tune, or distill LLMs. Through LLMAPI you reach 7 Meta models on the same OpenAI-compatible endpoint as every other provider, so switching between them is a one-string change.
Good fit for
- Text Generation
- Open-Weight Models
- Best for Local Deployment
- Self-Hosted / On-Premise
- Fine-Tunable Models
- Most Transparent
Consider another provider for
- No code generation models in this catalog
- No image generation models in this catalog
- No vision models in this catalog
- No video generation models in this catalog
- Not eligible for LLMAPI volume discounts
Key facts
Where a provider does not document something we say so rather than guess. Everything LLMAPI records about Meta, in one table.
Overview | |
| Provider | Meta |
| Website | meta.com |
| Best for | Self-hosting, fine-tuning, and keeping full control of model weights |
| Models on LLMAPI | 7 |
| Popular models | Llama 4 Maverick, Llama 4 Scout, Llama 3.3 70B, Llama 3.3 8B, Llama 3.1 405B, Llama 3.1 70B |
Access & routing | |
| API compatibility | OpenAI-compatible — /v1/chat/completions |
| Model ID prefix | meta/<model> |
| Regions | Self-hosted |
| Fallback | Configurable — on 429 or 5xx the router switches to any other model or provider on your list |
| Billing | One invoice across every provider, with per-key spend limits |
| Volume discount | Not eligible |
Performance (median across listed models) | |
| Blended price / 1M | $0.15 |
| Uptime (24h) | 99.95% (median across listed models) |
Modality | |
| Tags | |
Deployment | |
| Tags | |
Trust & safety | |
| Tags | |
Audience | |
| Tags | |
Privacy & data | |
| Inference location | Self-hosted |
| Data residency | Not documented by the provider |
| Default retention | Not documented by the provider |
| Zero-data retention | Not documented by the provider |
| Training on API data | Not documented by the provider |
| Human review | Not documented by the provider |
Compliance & lifecycle | |
| Certifications | ISO 27001 |
| Deprecation notice | Not documented by the provider |
| Operational status | Operational Live status |
Prices and context from the OpenRouter public catalogue; uptime and output speed from OpenRouter provider endpoints; quality scores from LiveBench. Refreshed nightly — last updated 2026-09-29. — means no figure is published for that model.
Best Meta models
A quick view of how Meta 's 7 models compare on intelligence, output speed and price — so you can pick the right one for your use case.
Most intelligent
#1Llama 4 Scout42
#2Llama 3.1 405B41
#3Llama 3.3 70B34
#4Llama 4 Maverick30
Intelligence index · 7 models
Fastest
#1Llama 3.1 405B425 t/s
#2Llama 3.1 8B425 t/s
#3Llama 3.1 70B418 t/s
#4Llama 3.3 70B386 t/s
Output tokens / second · 7 models
Lowest price
#1Llama 3.1 8B$0.56
#2Llama 3.1 405B$3.49
#3Llama 4 Maverick$7.91
#4Llama 4 Scout$9.89
Blended price per 1M tokens · 7 models
Compared with other hosts
How Meta sits against the rest of the catalog, using the same measurements shown on every provider page.
- Price. Median blended price of $9.89 per 1M tokens — 61% above the $6.13 median across all 50 providers in the catalog.
- Throughput. Median output speed of 386 tokens/s, 11% faster than the 348 tok/s catalog median.
- Catalog depth. 7 models listed, against a catalog average of 5 per provider.
- Integration. Identical to every other provider here — same endpoint, same SDK, same keys, so a switch costs one string change.
Median blended price per 1M tokens
lower is better| Meta | $9.89 | |
| DigitalOcean | $9.25 | |
| xAI (SpaceXAI) | $10.60 | |
| Parasail | $8.93 | |
| InclusionAI | $8.76 | |
| Nebius | $8.66 |
Median output speed
higher is better| Meta | 386 tok/s | |
| DigitalOcean | 348 tok/s | |
| xAI (SpaceXAI) | 242 tok/s | |
| Parasail | 822 tok/s | |
| InclusionAI | 244 tok/s | |
| Nebius | 580 tok/s |
Figures are medians across the models listed on each provider page and are refreshed with the catalog.
Models & pricing
Every Meta model reachable with your LLMAPI key. Click a column heading to sort.
| Model | API model name | Uptime 24h | Price / 1M | Context |
|---|---|---|---|---|
| Llama 4 Maverick | meta/llama-4-maverick | 99.95% | $ 0.3 | 1049 k |
| Llama 4 Scout | meta/llama-4-scout | 99.94% | $ 0.15 | 1311 k |
| Llama 3.3 70B | meta/llama-3-3-70b | 99.80% | $ 0.15 | 131 k |
| Llama 3.3 8B | meta/llama-3-3-8b | — | — | — |
| Llama 3.1 405B | meta/llama-3-1-405b | — | — | — |
| Llama 3.1 70B | meta/llama-3-1-70b | 99.99% | $ 0.4 | 131 k |
| Llama 3.1 8B | meta/llama-3-1-8b | 100.00% | $ 0.06 | 131 k |
Price is a blended per-1M-token figure; latency is time to first token and throughput is output tokens per second, measured on the LLMAPI edge.
Cost calculator
Pick a model, enter your traffic, and see the monthly bill at LLMAPI rates.
Estimates use the blended per-1M-token price shown in the table above. Word counts differ by language — Cyrillic and CJK text uses 2–3× more tokens per word.
Meta via LLMAPI
Same models, same features, one key. Prefix the model ID with meta/ and point your OpenAI client at our base URL.
# Python · OpenAI SDK from openai import OpenAI client = OpenAI( base_url="https://api.llmapi.ai/v1", api_key="LLMAPI_KEY", ) r = client.chat.completions.create( model="meta/llama-4-maverick", messages=[{"role": "user", "content": "Hello"}], )
| Pricing | Billed at the rates in the table above, on one invoice with every other provider. |
| Features | Full pass-through — tool calling, JSON schema, streaming, vision and reasoning behave exactly as on Meta’s own API. |
| Fallback | Configurable. On 429 or 5xx the router switches to any model or provider on your fallback list. |
| Regions | Self-hosted |
| Your data | LLMAPI stores request metadata only — model, token counts, latency and status. No prompt or completion content. |
Capabilities & use cases
Each tag below is its own catalog page listing every provider that shares it.
Developer resources
Where to go next.
Join thousands of developers building on one API key
Every provider in the catalog, one key, one invoice.
Questions
How do I call Meta models through LLMAPI?
Point any OpenAI-compatible client at https://api.llmapi.ai/v1 and use the model ID meta/llama-4-maverick. No other change is needed.
Does Meta cost more through LLMAPI?
No. You pay the rates shown in the table above, on a single invoice with every other provider.
Which regions are used?
Self-hosted
What happens if the provider returns an error?
On 429 or 5xx responses the router falls back to any other model or provider on your configured list, so requests keep succeeding.
How many Meta models are available?
7 at the moment, all listed in the models table above and updated as the provider ships new ones.
Related providers
Providers covering similar use cases.