Inteligencia de modelos de IA

Llama 3.1 405B Instruct Turbo

meta/llama-3-1-405b-instruct-turbo

Por Meta · familia: llama · lanzado 2024-07-23

$3.50
Entrada / 1M tokens
$3.50
Salida / 1M tokens
128K
Ventana de contexto
4K
Salida máxima

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Capacidades

✓ Llamada a herramientas✗ Razonamiento? Salida estructurada✗ Adjuntos✓ Pesos abiertos✓ Control de temperatura
Modalidades: entrada text · salida text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding43
  • Tool calling40/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)2/20
  • Provider availability1/10
Agents36
  • Tool calling35/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit0/15
  • Provider availability1/10
JSON / structured output36
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume6/20
Cost efficiency41
  • Headline price (log-scaled)41/95
  • Has prompt-cache pricing0/5
Long context45
  • Context window (100K → 2M)35/90
  • Has published price for full window10/10
Production-readiness65
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$19.25
$0.02 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$38.50
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$8.75
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$31.50
$0.03 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$44.10
$0.04 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Detalle de precios

Precio recomendado de abacus · meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo

$3.50
Entrada
$3.50
Salida

Disponible en 1 proveedores

ProveedorID de modelo del proveedorEntrada / 1MSalida / 1MContextoLanzado
Abacus
abacus
meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo$3.50$3.50128K2024-07-23

Frequently asked questions

How much does Llama 3.1 405B Instruct Turbo cost?

Llama 3.1 405B Instruct Turbo costs $3.50 per 1M input tokens and $3.50 per 1M output tokens, sourced from abacus. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Llama 3.1 405B Instruct Turbo?

Llama 3.1 405B Instruct Turbo has a context window of 128K tokens, with a max output of 4K tokens per reply. This is the total combined size of prompt + completion.

Does Llama 3.1 405B Instruct Turbo support tool calling?

Yes. Llama 3.1 405B Instruct Turbo supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Llama 3.1 405B Instruct Turbo support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for Llama 3.1 405B Instruct Turbo in our data source. Verify with Meta's official documentation before relying on it in production.

Can Llama 3.1 405B Instruct Turbo accept image input?

No. Llama 3.1 405B Instruct Turbo only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Llama 3.1 405B Instruct Turbo open-weight?

Yes. Llama 3.1 405B Instruct Turbo's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Llama 3.1 405B Instruct Turbo?

If Llama 3.1 405B Instruct Turbo doesn't fit, consider Meta-Llama-3.1-8B-Instruct, Llama-3.3-70B-Instruct, Llama 4 Maverick 17B 128E Instruct FP8. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

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See also

Última actualización:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.