Ministral 3 14B API pricing 2512
Published on-demand rates for Mistral's mistral/ministral-3-14b-2512, captured 2026-09-21 from public pricing data and committed to our archive. Context window 262k tokens; first observed in our archive 2026-03-02.
| Meter | USD per 1M tokens |
|---|---|
| Input | $0.200 |
| Output | $0.200 |
| Cached input | $0.020 |
Standard on-demand rates. Excludes batch endpoints and negotiated pricing; confirm on Mistral's pricing page before committing.
What it costs on a real workload
Per 1M tokens processed, at the rates above. How the four profiles are defined.
| Profile | In / out mix | Cached share | Cost |
|---|---|---|---|
| Retrieval | 800k / 200k | 70% | $0.099 |
| Chat | 500k / 500k | 30% | $0.173 |
| Content | 200k / 800k | 20% | $0.193 |
| Agent | 900k / 100k | 85% | $0.062 |
Observed rate history
| Observed | Input | Output | Cached input | |
|---|---|---|---|---|
| 2026-03-02 | $0.200 | $0.200 | — | entered our archive |
| 2026-08-30 | $0.200 | $0.200 | $0.020 | repricing observed |
Dates are when we observed the rate in our own snapshots, which can lag the provider's announcement. Rates per 1M tokens.
What the record shows
We have observed one change to Ministral 3 14B's rates since it entered our archive on 2026-03-02. The most recent, on 2026-08-30, left the output rate unchanged.
Against the 40 models we price, it is the 5th cheapest for retrieval-shaped work, which reads a great deal and writes little, and the 3rd cheapest for content-shaped work, which does the reverse. The two are close, so it holds its position whichever way your workload leans.
It charges the same rate for output as for input. That is unusual: 4 of the 40 models we price do it, and everywhere else output costs a median of 5.0 times input. On this model the length of the answer costs no more per token than the length of the question, which changes which workloads suit it.
Inside Mistral's own lineup it is the 3rd cheapest of the 10 models we track on this workload, so 2 cheaper and 7 more expensive options sit on the same account behind the same key.
22 of the 40 models we price offer a larger context window, and 4 match it exactly. Context is a capability limit rather than a cost one: paying more buys no extra room unless the larger window is what you are paying for.
Cached input reads at $0.020 against a standard input rate of $0.200, a 90% discount on the part of your prompt that repeats.
It accepts image input, but Mistral publishes no rule for how images become tokens, so we will not price a scanned page on it. That is a gap in the provider's documentation rather than a limit of the model, and it is the reason this model is excluded from image estimates in our estimator instead of being given a plausible figure.
Its 262k token context window holds roughly 197,000 words of English text in a single request. A workload that does not fit cannot run here at any price, which is a capability limit rather than a cost one.
Priced near this one
Closest to Ministral 3 14B on a retrieval workload, cheaper and more expensive alike. Cost only; we publish no quality score.
| Model | Provider | Input | Output | vs Ministral 3 14B |
|---|---|---|---|---|
| GPT 5 Nano | OpenAI | $0.050 | $0.400 | 4% less |
| Gemini 2.5 Flash Lite | $0.100 | $0.400 | 10% more | |
| Gemini 2.0 Flash Lite | $0.075 | $0.300 | 11% less | |
| Ministral 3 8B | Mistral | $0.150 | $0.150 | 25% less |
Retrieval profile: 800k in, 200k out, 70% cached where offered.
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