Inteligencia de modelos de IA

R1 Distill Llama 70B

deepseek/r1-distill-llama-70b

Por DeepSeek · familia: deepseek-thinking · lanzado 2025-01-23 · fecha de conocimiento: 2024-07-31

$0.030
Entrada / 1M tokens
$0.140
Salida / 1M tokens
8K
Ventana de contexto
8K
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.

Coding14
  • Tool calling0/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)0/20
  • Provider availability4/10
Agents24
  • Tool calling0/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit5/15
  • Provider availability4/10
JSON / structured output30
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control10/10
  • Price-friendly for high-volume20/20
Cost efficiency81
  • Headline price (log-scaled)81/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness71
  • Number of independent providers20/40
  • Has published per-token price20/20
  • Context window ≥ 8K8/15
  • No data inconsistencies across providers8/10
  • 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
$0.22
< $0.01 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
$0.44
< $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
$0.13
< $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
$0.38
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$0.44
< $0.01 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 fastrouter · deepseek-ai/deepseek-r1-distill-llama-70b

$0.030
Entrada
$0.140
Salida

Disponible en 4 proveedores

ProveedorID de modelo del proveedorEntrada / 1MSalida / 1MContextoLanzado
OpenRouter
openrouter
deepseek/deepseek-r1-distill-llama-70b$0.800$0.8008K2025-01-23
NovitaAI
novita-ai
deepseek/deepseek-r1-distill-llama-70b$0.800$0.8008K2025-01-27
Kilo Gateway
kilo
deepseek/deepseek-r1-distill-llama-70b$0.700$0.800131K2025-01-23
FastRouter
fastrouter
deepseek-ai/deepseek-r1-distill-llama-70b$0.030$0.140131K2025-01-23

Inconsistencias de datos entre proveedores

  • context_window varies: 131072, 8192

Los proveedores reportan valores distintos para este modelo. Los datos clave de arriba usan un proveedor representativo; consulta la tabla para detalles por proveedor.

Frequently asked questions

How much does R1 Distill Llama 70B cost?

R1 Distill Llama 70B costs $0.030 per 1M input tokens and $0.140 per 1M output tokens, sourced from fastrouter. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of R1 Distill Llama 70B?

R1 Distill Llama 70B has a context window of 8K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.

Does R1 Distill Llama 70B support tool calling?

No. R1 Distill Llama 70B does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does R1 Distill Llama 70B support structured output / JSON mode?

No. R1 Distill Llama 70B does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can R1 Distill Llama 70B accept image input?

No. R1 Distill Llama 70B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is R1 Distill Llama 70B open-weight?

Yes. R1 Distill Llama 70B'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 R1 Distill Llama 70B?

If R1 Distill Llama 70B doesn't fit, consider DeepSeek V4 Pro, DeepSeek-V3.2, DeepSeek V4 Flash. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

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Capability lists this model is in

See also

Última actualización:

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.