Inteligencia de modelos de IA

Claude Opus 4.7 Thinking

aihubmix/claude-opus-4-7-think

Por aihubmix · familia: claude-opus · lanzado 2026-04-16 · fecha de conocimiento: 2026-01-31

⚠ Este es un ajuste fino de la comunidad o un derivado — no un lanzamiento oficial del editor.

$5.00
Entrada / 1M tokens
$25.00
Salida / 1M tokens
200K
Ventana de contexto
32K
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, image · 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.

Coding77
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)6/20
  • Provider availability1/10
Agents91
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output70
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control0/10
  • Price-friendly for high-volume0/20
Cost efficiency31
  • Headline price (log-scaled)26/95
  • Has prompt-cache pricing5/5
Long context55
  • Context window (100K → 2M)45/90
  • Has published price for full window10/10
Vision81
  • Accepts image input50/50
  • Context window (10K → 1M)20/30
  • Has published price10/10
  • Provider availability1/10
Production-readiness50
  • 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)0/15

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
$37.50
$0.04 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
$75.00
< $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
$22.50
$0.02 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
$65.00
$0.07 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$75.00
$0.07 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 aihubmix · claude-opus-4-7-think

$5.00
Entrada
$25.00
Salida
$0.500
Lectura de caché
$6.25
Escritura de caché

Disponible en 1 proveedores

ProveedorID de modelo del proveedorEntrada / 1MSalida / 1MContextoLanzado
AIHubMix
aihubmix
claude-opus-4-7-think$5.00$25.00200K2026-04-16

Frequently asked questions

How much does Claude Opus 4.7 Thinking cost?

Claude Opus 4.7 Thinking costs $5.00 per 1M input tokens and $25.00 per 1M output tokens, sourced from aihubmix. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Claude Opus 4.7 Thinking?

Claude Opus 4.7 Thinking has a context window of 200K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.

Does Claude Opus 4.7 Thinking support tool calling?

Yes. Claude Opus 4.7 Thinking 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 Claude Opus 4.7 Thinking support structured output / JSON mode?

Yes. Claude Opus 4.7 Thinking supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Claude Opus 4.7 Thinking accept image input?

Yes. Claude Opus 4.7 Thinking accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check aihubmix's docs for the exact rule.

Is Claude Opus 4.7 Thinking open-weight?

No. Claude Opus 4.7 Thinking is a proprietary model — only aihubmix (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Claude Opus 4.7 Thinking?

If Claude Opus 4.7 Thinking doesn't fit, consider o4-mini. 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.

Explore more

More aihubmix models

Capability lists this model is in

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.