Mistral: Mistral Small 3.2 24B

mistralai/mistral-small-3.2-24b-instruct

Modalities: text+image->text
In / out price: $0.094 / $0.25
Context: 256K
Released: Jun 20, 2025
Knowledge cutoff: 2023-10-31

Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...

VisionToolsStructured outputLong context

Supported parameters

frequency_penalty
Frequency penalty
Lowers the chance of a token in proportion to how often it already appeared.
logit_bias
Logit bias
Add or subtract from token ids to encourage or ban them.
logprobs
Logprobs
Return the log probability of each output token.
max_tokens
Max tokens
Upper bound on generated tokens. Output stops at the limit.
min_p
Min-p
Drops tokens below this probability threshold.
presence_penalty
Presence penalty
Lowers the chance of any token that has already appeared.
repetition_penalty
Repetition penalty
Penalizes text that already appeared. Common on open models.
response_format
Response format
For example json_object or json_schema, to constrain the shape.
seed
Seed
A fixed seed helps reproduce sampling. It does not guarantee byte-identical output.
stop
Stop
Stop when these strings are produced. A string or an array of strings.
structured_outputs
Structured outputs
Generate a parseable structure that follows a JSON Schema.
temperature
Temperature
Sampling temperature. Lower is steadier, higher is more varied. Often 0 to 2.Default 0.3
tool_choice
Tool choice
Whether to call a tool: auto, none, or a named function.
tools
Tools
Function definitions the model may call via tool_calls.
top_k
Top-K
Sample only from the K most likely tokens.
top_logprobs
Top logprobs
Also return the most likely alternatives at each position.
top_p
Top-p
Sample only from tokens whose cumulative probability reaches top_p.

Supported parameters

frequency_penalty

Frequency penalty

Lowers the chance of a token in proportion to how often it already appeared.

logit_bias

Logit bias

Add or subtract from token ids to encourage or ban them.

logprobs

Logprobs

Return the log probability of each output token.

max_tokens

Max tokens

Upper bound on generated tokens. Output stops at the limit.

min_p

Min-p

Drops tokens below this probability threshold.

presence_penalty

Presence penalty

Lowers the chance of any token that has already appeared.

repetition_penalty

Repetition penalty

Penalizes text that already appeared. Common on open models.

response_format

Response format

For example json_object or json_schema, to constrain the shape.

seed

Seed

A fixed seed helps reproduce sampling. It does not guarantee byte-identical output.

stop

Stop

Stop when these strings are produced. A string or an array of strings.

structured_outputs

Structured outputs

Generate a parseable structure that follows a JSON Schema.

temperature

Temperature

Sampling temperature. Lower is steadier, higher is more varied. Often 0 to 2.Default 0.3

tool_choice

Tool choice

Whether to call a tool: auto, none, or a named function.

tools

Tools

Function definitions the model may call via tool_calls.

top_k

Top-K

Sample only from the K most likely tokens.

top_logprobs

Top logprobs

Also return the most likely alternatives at each position.

top_p

Top-p

Sample only from tokens whose cumulative probability reaches top_p.