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Mistral: Mistral Medium 3.5 (batch) API Pricing

Mistral: Mistral Medium 3.5 (batch) costs $0.750 per 1M input tokens and $3.75 per 1M output tokens. Context window: 262K. Prices verified 2026-10-21 · source

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Price history
2026-08-28 → 2026-10-21 · 59 daily snapshots
inputoutput

Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.

Pricing behavior
Stable — no price moves across our 59 daily snapshots (2026-08-23 → 2026-10-21).

From our own daily snapshot archive — independent of provider announcements.

Intelligence & capability
via Artificial Analysis
14.2
Intelligence index · top 63% of 288 scored
46.9
Coding index
7
Agentic index
$1.5
Blended $/1M (3:1 in:out)

Intelligence measures reasoning/knowledge/coding benchmarks. A high score with a low blended price = value pick; check the value chart to see where this model lands.

Input / 1M tokens
$0.750
Output / 1M tokens
$3.75
Context window
262K
Max output
210K
Reasoning behavior
Mode: Off by default (opt-in)
Effort levels:highnone

Higher effort = deeper thinking = more reasoning tokens billed as output.

What would Mistral: Mistral Medium 3.5 (batch) cost you per month?

WorkloadRequests/moAvg tokens (in/out)Est. monthly cost
Light chatbot10,000800 / 400$21.00
Coding agent5,0008,000 / 2,000$67.50
RAG pipeline30,0004,000 / 500$146.25
Doc summarizer2,00020,000 / 1,000$37.50

Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.

About Mistral: Mistral Medium 3.5 (batch)

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...

Compare Mistral: Mistral Medium 3.5 (batch) with

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Frequently asked questions

How much does Mistral: Mistral Medium 3.5 (batch) cost?

Mistral: Mistral Medium 3.5 (batch) costs $0.750 per 1M input tokens and $3.75 per 1M output tokens. Verified 2026-10-21 — provider source.

What is the context window?

262K tokens, with up to 210K output tokens per response. That's roughly 328 pages of text in a single request.

Does it support prompt caching?

Prompt-caching pricing is not published for this model via OpenRouter.

What's a cheaper alternative?

ScaleDown: Summarize saves about 98% on a typical workload with comparable quality.

Official resources