Интерфейс моделей ИИ

Mixtral 8x7B Instruct v0.1

cortecs/mixtral-8x7b-instruct-v0-1

От cortecs · выпуск 2023-12-11 · дата знаний: 2023-09

⚠ Это сообществом дообученная / производная модель — не официальный релиз вендора.

$0.488
Вход / 1M токенов
$0.758
Выход / 1M токенов
32K
Окно контекста
32K
Макс. вывод

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

Возможности

Tool callingРассуждениеСтруктурированный выводВложенияОткрытые весаУправление температурой
Модальности: вход text · выход 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.

Coding31
  • Tool calling0/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)0/20
  • Provider availability1/10
Agents56
  • Tool calling0/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output78
  • Structured output / JSON mode50/50
  • Tool calling0/20
  • Temperature control10/10
  • Price-friendly for high-volume18/20
Cost efficiency60
  • Headline price (log-scaled)60/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
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
$2.82
< $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
$5.64
< $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
$1.35
< $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
$4.66
< $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
$6.31
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Детализация цен

Рекомендованная цена от cortecs · mixtral-8x7B-instruct-v0.1

$0.488
Вход
$0.758
Выход

Доступна у 1 провайдеров

ПровайдерID модели провайдераВход / 1MВыход / 1MКонтекстВыпуск
Cortecs
cortecs
mixtral-8x7B-instruct-v0.1$0.488$0.75832K2023-12-11

Frequently asked questions

How much does Mixtral 8x7B Instruct v0.1 cost?

Mixtral 8x7B Instruct v0.1 costs $0.488 per 1M input tokens and $0.758 per 1M output tokens, sourced from cortecs. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Mixtral 8x7B Instruct v0.1?

Mixtral 8x7B Instruct v0.1 has a context window of 32K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.

Does Mixtral 8x7B Instruct v0.1 support tool calling?

No. Mixtral 8x7B Instruct v0.1 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does Mixtral 8x7B Instruct v0.1 support structured output / JSON mode?

Yes. Mixtral 8x7B Instruct v0.1 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 Mixtral 8x7B Instruct v0.1 accept image input?

No. Mixtral 8x7B Instruct v0.1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Mixtral 8x7B Instruct v0.1 open-weight?

Yes. Mixtral 8x7B Instruct v0.1'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 Mixtral 8x7B Instruct v0.1?

If Mixtral 8x7B Instruct v0.1 doesn't fit, consider Nova Pro 1.0, voxtral-small-2507, ministral-8b-2512. 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.

More cortecs models

Capability lists this model is in

Последнее обновление:

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