AI 모델 인텔리전스

Mixtral 8x22B

mistral/mixtral-8x22b-instruct

제공: Mistral · 패밀리: mixtral · 출시 2024-04-17 · 지식 컷오프: 2024-04

$2.00
입력 / 1M 토큰
$6.00
출력 / 1M 토큰
64K
컨텍스트 창
64K
최대 출력

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

기능

도구 호출추론? 구조화 출력첨부오픈 웨이트온도 제어
모달리티: 입력 text · 출력 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)0/20
  • Provider availability3/10
Agents53
  • Tool calling35/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability3/10
JSON / structured output34
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume4/20
Cost efficiency40
  • Headline price (log-scaled)40/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness73
  • Number of independent providers15/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • 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
$13.00
$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
$26.00
< $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
$7.00
< $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
$22.00
$0.02 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$27.60
$0.03 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

가격 상세

추천 가격 제공자: vercel · mistral/mixtral-8x22b-instruct

$2.00
입력
$6.00
출력

가장 저렴한 제공자: nvidia · Unknown 입력 + Unknown 출력

3곳 제공사에서 이용 가능

제공자제공자 모델 ID입력 / 1M출력 / 1M컨텍스트출시일
Vercel AI Gateway
vercel
mistral/mixtral-8x22b-instruct$2.00$6.0064K2024-04-17
Kilo Gateway
kilo
mistralai/mixtral-8x22b-instruct$2.00$6.0066K2024-04-17
Nvidia
nvidia
mistralai/mixtral-8x22b-instructUnknownUnknown66K2024-04-17

제공자 간 데이터 불일치

  • context_window varies: 64000, 65536

제공자별로 이 모델의 값이 다릅니다. 위의 핵심 정보는 대표 제공자 기준이며, 제공자별 상세는 표를 참고하세요.

Frequently asked questions

How much does Mixtral 8x22B cost?

Mixtral 8x22B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens, sourced from vercel. 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 8x22B?

Mixtral 8x22B has a context window of 64K tokens, with a max output of 64K tokens per reply. This is the total combined size of prompt + completion.

Does Mixtral 8x22B support tool calling?

Yes. Mixtral 8x22B 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 Mixtral 8x22B support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for Mixtral 8x22B in our data source. Verify with Mistral's official documentation before relying on it in production.

Can Mixtral 8x22B accept image input?

No. Mixtral 8x22B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Mixtral 8x22B open-weight?

Yes. Mixtral 8x22B'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 8x22B?

If Mixtral 8x22B doesn't fit, consider Mistral Nemo Instruct 2407, Mistral Nemo, Mistral Large 2.1. 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.

More Mistral models

Capability lists this model is in

마지막 업데이트:

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.