Mistral

mistral-nemo

Estimated pricingMedium memory

mistral-nemo is Mistral's medium-memory model. This page shows current pricing, an interactive cost calculator, and a side-by-side with similar models.

Input

$0.20/1M tokens

Output

$0.40/1M tokens

Cached

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Batch

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Interactive

Calculate your mistral-nemo bill.

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What would mistral-nemo cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

mistral-nemo at a glance.

Memory

131,000

tokens

Max reply

—

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

default

Released

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Training cutoff

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Availability

Estimated

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick mistral-nemo

  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.
  • You need tool-use / function calling for agent workflows.

Alternatives

Similar models to compare.

FAQ

mistral-nemo — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, mistral-nemo costs roughly $31 per month. Input is $0.20 /1M tokens and output is $0.40 /1M tokens.
mistral-nemo has a 131,000-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,563 words of input and history in a single call.
Models in a similar class include qwen3.5-2b, llama-3.2-1b-instruct, llama-3.1-8b-instruct. The "Similar models" section below this FAQ links into each.
Open-weight model — price from a common hosting provider (Together, Fireworks, Replicate). We source estimates from the cheapest public hosting provider for that model and note it on the page.

Still unsure?

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