leanstral-1-5

Name: leanstral-1-5
Brand: Mistral AI SAS
SKU: mistral/leanstral-1-5
Availability: InStock

Leanstral 1.5 is an updated Lean 4 formal proof engineering model from Mistral AI, optimized for automated theorem proving and autoformalization. It has 119B total parameters with 6.5B active and supports a 256K token context window. It supports native function calling and structured output.More

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Which id to call

mistral/leanstral-1-5

This exact deployment on Mistral AI SAS, with no routing and no failover. Send it as the model field.

Input /1M

free

Mistral AI SAS

Output /1M

free

no charge

Context

262K

33K output

Added

May 2026

chat

Capabilities 2/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What leanstral-1-5 costs

Provider prices per 1M tokens, updated October 2, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

free

Output /1M

free

Cache write /1M

Cache read /1M

What a workload costs

100K input + 10K output: free
1M input + 100K output: free
10M input + 1M output: free

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

mistral/leanstral-1-5

This exact deployment on Mistral AI SAS, with no routing and no failover. Send it as the model field.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="mistral/leanstral-1-5",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Live from production

Mistral AI SAS on leanstral-1-5, measured

What this provider was measured doing on leanstral-1-5 across Requesty traffic.more

Whole-window figures, because that is the grain published per provider. They cover Mistral AI SAS serving this model in every region it serves it from, so a region-pinned deployment shares them with its siblings. A figure is absent where no qualifying sample exists.

First token

1.54s

median

p95 wait

8.45s

slowest 5%

Cache hit

63.3%

of input tokens

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window262K tokens

Max output33K tokens

API typechat

AddedMay 2026

Model id

Data retentionNone

Used for trainingNo

Served from🇪🇺 EU

Privacy policyMistral Privacy Policy →

Released 2023-12-11

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

GPQA Diamondreasoning

34.9%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning

5.5%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Same provider

More from Mistral AI SAS

Newest first, on the same provider and the same key.

glm-5-2

1M ctx/$1.54/1M

devstral-latest

256K ctx/$0.44/1M

mistral-medium-3-5

262K ctx/$1.65/1M

mistral-medium-latest

131K ctx/$0.44/1M

mistral-small-latest

256K ctx/$0.17/1M

mistral-small-2603

256K ctx/$0.17/1M

Reference

leanstral-1-5 questions

How much does leanstral-1-5 cost?

leanstral-1-5 is priced at free per million input tokens and free per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of leanstral-1-5?

leanstral-1-5 has a context window of 262K tokens, with a maximum output of 33K tokens per response. That's roughly 350 words of input you can fit in a single prompt.

How does leanstral-1-5 perform on benchmarks?

leanstral-1-5 scores 49.1% on MMLU Pro, 34.9% on GPQA Diamond, 9.9% on LiveCodeBench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.

What can leanstral-1-5 do?

leanstral-1-5 supports tool calling, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use leanstral-1-5 with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "mistral/leanstral-1-5". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run leanstral-1-5 through Requesty?

Yes. leanstral-1-5 runs through Requesty's OpenAI-compatible API, served from Mistral AI SAS. You do not host the model yourself: point base_url at Requesty, set the model to "mistral/leanstral-1-5", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call leanstral-1-5 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All Mistral AI SAS models