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MistralReleased September 18, 2025

Magistral Medium 1.2

Mistral · Released September 18, 2025

Intelligence score

18

At a glance

Intelligence
18
Speed
39.6tokens/sec
Latency
1.77stime to first token
Input price
$2.00per 1M tokens
Output price
$5.00per 1M tokens
Context window
130Ktokens
Parameters
—

Summary

Comparison summary

Magistral Medium 1.2 scores 18 on the Artificial Analysis Intelligence Index, placing it below average among other reasoning models in a similar price tier (median: 28). Magistral Medium 1.2 generates output at 39.6 tokens per second (based on Mistral's API), which is at the lower end compared to other reasoning models in a similar price tier (median: 81.2 t/s). Magistral Medium 1.2 costs $2.00 per 1M input tokens (somewhat higher than average, median: $1.50) and $5.00 per 1M output tokens (better than average, median: $8.40), based on Mistral's API.

Specifications

Technical specifications

Model nameMagistral Medium 1.2
ProviderMistral
Release dateSeptember 18, 2025
Intelligence score18
Speed39.6 tokens/sec
Latency (TTFT)1.77s
Input price$2.00 / 1M tokens
Output price$5.00 / 1M tokens
Context window130,000 tokens
Parameters—
ReasoningYes
Input modalitiestext, image
Output modalities—
Open weightsNo
License—
API availability—
SourceModel Intelligence legacy profile: magistral-medium-2509

Pricing

Token prices

Price per 1M tokens

Magistral Medium 1.2, as listed in the catalog record

Input $2.00 and output $5.00 per 1M tokens. Missing prices are hatched and marked "Not published".
  1. Input$2.00
  2. Output$5.00

Model Intelligence legacy profile: magistral-medium-2509

FAQ · 19

Frequently asked questions

Magistral Medium 1.2 was released on September 18, 2025.

Magistral Medium 1.2 was created by Mistral.

Magistral Medium 1.2 scores 18 on the Artificial Analysis Intelligence Index, placing it below average among other reasoning models in a similar price tier (median: 28).

Magistral Medium 1.2 generates output at 39.6 tokens per second (based on Mistral's API), which is at the lower end compared to other reasoning models in a similar price tier (median: 81.2 t/s).

Magistral Medium 1.2 has a time to first token (TTFT) of 1.77s (based on Mistral's API), which is better than average compared to other reasoning models in a similar price tier (median: 2.78s).

Magistral Medium 1.2 costs $2.00 per 1M input tokens (somewhat higher than average, median: $1.50) and $5.00 per 1M output tokens (better than average, median: $8.40), based on Mistral's API.

Magistral Medium 1.2 costs $2.00 per 1M input tokens and $5.00 per 1M output tokens (based on Mistral's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $2.30 per 1M tokens. Pricing may vary by provider.

When evaluated on the Intelligence Index, Magistral Medium 1.2 generated 44M output tokens, which is better than average compared to other reasoning models in a similar price tier (median: 72M).

Yes, Magistral Medium 1.2 is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Magistral Medium 1.2 supports text and image input.

Magistral Medium 1.2 supports text output.

Yes, Magistral Medium 1.2 supports image input and can analyze, describe, and answer questions about images.

Yes, Magistral Medium 1.2 is multimodal. It can process text and image input and generate text output.

Magistral Medium 1.2 has a context window of 130k tokens. This determines how much text and conversation history the model can process in a single request.

No, Magistral Medium 1.2 is proprietary. The model weights are not publicly available.

Magistral Medium 1.2 is a proprietary model and Mistral has not disclosed the model size or parameter count.

Magistral Medium 1.2 achieves a score of 18 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Yes, Magistral Medium 1.2 is available via API through 1 provider.

Magistral Medium 1.2 is available through 1 API provider.