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AI Model Atlas / Mistral AI

Mistral Nemo

One million input tokens cost $0.029 and one million output tokens $0.030. Context window: 131k tokens, about 218 A4 pages.

Data from 11 November 2026 API identifier: mistralai/mistral-nemo

What it costs in practice

Pricing per million tokens doesn't mean anything to anyone, so I convert it to three tasks that people actually give to models. The usage assumptions are listed for each row so you can verify them.

TaskInputOutputCost
1500-word articlebrief plus finished text in English 1,500 tokens 2,200 tokens $0.0001
100 chat queries700 tokens per question and 400 per answer 70,000 tokens 40,000 tokens $0.0032
Hour of work with an agentagent reads repository and writes fixes 250,000 tokens 30,000 tokens $0.0082
The calculation does not include tax, intermediary markup, or context caching, which with repeated prompts can cut input costs by several dozen percent.

Technical details

ProviderMistral AI
Modalitiestext → text
Context window131k tokens (~218 A4 pages)
Maximum response16k tokens
Step-by-step reasoningno
Tool callingyes
Forced JSON formatyes
Knowledge cutoff2024-04-30
Cache readno data
Content moderationno extra filter

How it compares to the rest

The database contains 469 models. In terms of input pricing Mistral Nemo is more expensive than 2 percent of paid models. A longer context window is available in 363 models.

Input price history

2026-09-08 · $0.0192026-11-11 · $0.029

The chart shows the price of a million input tokens on consecutive measurement days. History starts on the day I launched the atlas and grows with each day. I don't backfill data.

Alternatives at a similar price

Models from other providers whose cost for the same article comes out closest.

ModelInput / MOutput / M1500-word articleContext
Llama 3.1 8B InstructMeta $0.020 $0.040 $0.0001 131k
Ling 3.0 TinyInclusionai $0.015 $0.045 $0.0001 262k
SummarizeScaledown $0.040 free $0.0001 1M
ExtractScaledown $0.040 free $0.0001 1M

Compare Mistral Nemo with another model or go back to the full database 469 models.

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