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CostPerPrompt

Mistral Large API Pricing

Mistral · context window 128K · prices updated 2026-09-15

Input per 1M tokens
$2.00
Output per 1M tokens
$6.00
Cached input per 1M
$0.2
90% cheaper than fresh input

Where Mistral Large sits on price

At $6.00 per million output tokens, Mistral Large is a premium tier model — 2.9× the median output price of $2.08, which puts it cheaper than 29% and pricier than 71% of the models we track. It sits 24th cheapest of the 25 Mistral models we track. Output is only 3.0× the input price, an unusually flat spread: long prompts hurt about as much as long answers, so prompt size is where the savings are.

Output tokens per $1
166,667
One full context fill
$0.256
Cheaper than
29% of tracked models

Cached input is 90% cheaper. On an input-heavy workload you need roughly a 28% cache-hit rate to take 25% off the input line — reachable for chatbots and agents that resend the same system prompt and history.

What real workloads cost on Mistral Large

These three workloads are the ones teams actually run on a premium-priced model — a $6.00/1M model is not bought for the same job as one ten times the price.

Workload Per request Per month
Support chatbot — 500 conversations/day (5K in / 1.4K out) Conversation history re-sent each turn — the classic prompt-caching win. $0.0184 $276
Coding agent — 300 sessions/day (60K in / 12K out) Multi-step loops re-read the same files; caching matters more than raw price. $0.192 $1728
Small app — 1K requests/day (500 in / 150 out) The baseline most side projects actually run at. $0.0019 $57.00

Model your exact traffic in the API cost calculator — it preloads Mistral Large with caching and batch options.

Mistral Large price history

Mistral Large's price has not moved since we began tracking it on Aug 2, 2026 — 44 days of stability in a market where 78 of the 334 models we track have repriced over the same period, including 7 of Mistral's own 25 models.

Change-points from our daily price snapshots (tracking since Aug 2, 2026; intraday moves between snapshots are not captured).

Mistral Large vs Qwen3.8 Max (0902)

The closest-priced alternative from another vendor is Qwen3.8 Max (0902) (Alibaba (Qwen)) — priced within a rounding error on output, with identical input pricing. When two models land this close on price, the decision is quality on your own workload, not the price sheet: run 50 real requests through both and compare.

See Qwen3.8 Max (0902) pricing →

Cheaper alternatives

More Mistral models

Frequently asked questions

How much does the Mistral Large API cost?

Mistral Large costs $2.00 per million input tokens and $6.00 per million output tokens, with cached input at $0.2 per million (90% cheaper). That works out to roughly 166,667 output tokens per dollar.

What does the support chatbot workload cost on Mistral Large?

Support chatbot — 500 conversations/day (5K in / 1.4K out) costs about $0.0184 per request and $276 per month on Mistral Large. Conversation history re-sent each turn — the classic prompt-caching win.

What does it cost to fill Mistral Large's 128K context window?

Sending 128K of input in a single request costs $0.256 at $2.00 per million tokens — before any output. With prompt caching that same fill drops to about $0.0256 on repeat requests. This is why large context windows are cheap to advertise and expensive to actually use.

Is Mistral Large worth the price?

Mistral Large sits in the middle of the market (24 of 25 by price within Mistral). The honest test is a routing experiment: send the same 200 real requests to this model and to a tier below, and compare failure rate against the price gap — most teams find a majority of traffic never needed the pricier model.