AI 模型情报

Mistral Nemo

mistral/nemo-instruct-2407

出品方: Mistral · 系列: mistral · 发布 2024-07-18 · 知识截止: 2024-05

$0.020
输入 / 1M token
$0.040
输出 / 1M token
128K
上下文长度
8K
最大输出

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

能力清单

工具调用推理结构化输出附件开放权重温度可调
支持模态: 输入 text · 输出 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.

Coding48
  • Tool calling40/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)2/20
  • Provider availability6/10
Agents46
  • Tool calling35/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit5/15
  • Provider availability6/10
JSON / structured output50
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume20/20
Cost efficiency96
  • Headline price (log-scaled)91/95
  • Has prompt-cache pricing5/5
Long context45
  • Context window (100K → 2M)35/90
  • Has published price for full window10/10
Production-readiness86
  • Number of independent providers30/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers6/10
  • 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
$0.12
< $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
$0.24
< $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
$0.06
< $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
$0.20
< $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
$0.26
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 io-net · mistralai/Mistral-Nemo-Instruct-2407

$0.020
输入
$0.040
输出
$0.010
缓存读
$0.040
缓存写

在 6 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
STACKIT
stackit
neuralmagic/Mistral-Nemo-Instruct-2407-FP8$0.490$0.710128K2024-07-01
DigitalOcean
digitalocean
mistral-nemo-instruct-2407$0.300$0.300128K2024-07-18
IO.NET
io-net
mistralai/Mistral-Nemo-Instruct-2407$0.020$0.040128K2024-07-01
OVHcloud AI Endpoints
ovhcloud
mistral-nemo-instruct-2407$0.140$0.14066K2024-11-20
Meganova
meganova
mistralai/Mistral-Nemo-Instruct-2407$0.020$0.040131K2024-07-18
NanoGPT
nano-gpt
mistralai/Mistral-Nemo-Instruct-2407$0.100$0.12116K2024-07-18

各渠道数据存在不一致

  • context_window varies: 128000, 131072, 16384, 65536
  • release_date varies (span 142d): 2024-07-01, 2024-07-18, 2024-11-20

各服务商对此模型的报告值存在差异。上方「核心数据」使用代表性服务商的值;逐项请以下表为准。

Frequently asked questions

How much does Mistral Nemo cost?

Mistral Nemo costs $0.020 per 1M input tokens and $0.040 per 1M output tokens, sourced from io-net. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Mistral Nemo?

Mistral Nemo has a context window of 128K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.

Does Mistral Nemo support tool calling?

Yes. Mistral Nemo 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 Mistral Nemo support structured output / JSON mode?

No. Mistral Nemo does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can Mistral Nemo accept image input?

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

Is Mistral Nemo open-weight?

Yes. Mistral Nemo'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 Mistral Nemo?

If Mistral Nemo doesn't fit, consider Mistral Nemo, Mistral Large 3, Devstral 2. 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 Mistral models

Capability lists this model is in

最近更新:

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