Mistral Models Guide: Large 4, Medium 3.5, Small 4 Compared

Mistral’s 2026 lineup centers on Mistral Large 4 for frontier work, Mistral Medium 3.5 for agentic coding, Mistral Small 4 for cheap all-round use, and Ministral 3 for small devices, and Small 4 and Ministral 3 ship under the Apache 2.0 license. Mistral Large 4 entered public preview on October 6, 2026 with open weights promised by the end of that month.

I read Mistral’s model overview, its pricing page, and the Large 4 announcement in October 2026, then scanned Reddit and Facebook discussion. My pick: start on Mistral Small 4 for most work, use Medium 3.5 for coding agents, and wait for the Large 4 weights before you plan a self-hosted deployment.

For a closed-model contrast, see our ChatGPT vs Mistral comparison.

How I Researched This Guide

Model names, versions, and licenses come from Mistral’s docs model overview, and Large 4 details and API prices come from Mistral’s announcement and pricing page, all checked in October 2026. Benchmarks in the Large 4 announcement are Mistral’s own and are labeled vendor-reported.

I did not run the models. Community signals come from r/LocalLLaMA thread titles and Facebook posts collected with Apify, and Quora searches returned no usable results in my run.

Which Mistral Models Are Current in 2026?

Mistral’s docs list 8 current general-purpose models, headed by Large 4 (v26.10), Medium 3.5 (v26.04), and Small 4 (v26.03), plus specialist models for OCR, audio, code, embeddings, moderation, and forecasting. The table covers the generalist line.

Model	Version	License	What Mistral says it does
Mistral Large 4	v26.10	Open weights (terms not yet published)	Multimodal, general-purpose; about 1T total and 52B active parameters
Mistral Medium 3.5	v26.04	Modified MIT	Multimodal, frontier-class, for agentic and coding work
Mistral Small 4	v26.03	Apache 2.0	Instruct, reasoning, and coding in one model
Mistral Large 3	v25.12	Apache 2.0	Multimodal, general-purpose
Ministral 3 14B	v25.12	Apache 2.0	Text and vision
Ministral 3 8B	v25.12	Apache 2.0	Text and vision, efficient
Ministral 3 3B	v25.12	Apache 2.0	Text and vision, small footprint

Mistral’s docs do not publish context windows or parameter counts for most of these models on the overview page, except the 14B, 8B, and 3B sizes in the Ministral names.

What Is Mistral Large 4?

Mistral Large 4 is a natively multimodal mixture-of-experts model with about 1 trillion total parameters and 52 billion active, announced as a public preview on October 6, 2026. Mistral says the weights release by the end of October 2026, without naming a license or a context window.

API pricing in the announcement is $1.36 per million input tokens and $4.18 per million output tokens. Mistral’s own benchmarks report 61.7% on DeepSWE v1.1 and 28.3% on Terminal-Bench 4.0.

In a blind coding study run with Surge AI, Large 4 ranked second of five at 3.74, behind Claude Opus 5 at 4.22. Those are vendor-reported results, so run your own tests before switching.

What Is Mistral Medium 3.5?

Mistral Medium 3.5 is a multimodal, frontier-class model for agentic and coding work, released as version 26.04 under a modified MIT license. It sits one tier below Large in Mistral’s naming.

The license matters. Mistral does not detail the modifications on the overview page, so read the license text on the model card before shipping a product.

Pick Medium 3.5 when Large 4 is overkill and you want agent and coding strength at a lower tier. For wider coding options, see our best AI chatbot for coding roundup.

What Is Mistral Small 4?

Mistral Small 4 combines instruct, reasoning, and coding in one model under the Apache 2.0 license, released as version 26.03. That removes the need to route between separate chat, reasoning, and code models.

Apache 2.0 allows commercial use, modification, and redistribution without a user-count cap, which makes Small 4 the cleanest legal fit in the lineup. It is the model I would test first on a new project.

What Are the Ministral 3 Models?

Ministral 3 comes in 3 sizes, 14B, 8B, and 3B parameters, all with text and vision input under Apache 2.0. Mistral released them as version 25.12 for efficient and small-footprint deployment.

The 3B model targets edge devices, the 8B model targets laptops and small servers, and the 14B model targets a single mid-range GPU. Those hardware pairings are my reading of the parameter counts, not Mistral guidance.

Which Specialist Mistral Models Exist?

Mistral lists specialist models in 6 areas: OCR, audio, code, embeddings, moderation, and time series. Most carry a “Premier” commercial license, and a few are open.

• OCR: OCR 4.1 (v4.1) and OCR 3 (v25.12), both Premier, for document OCR with bounding boxes and confidence scores.
• Audio: Voxtral TTS 3 and the Voxtral Transcribe 3 family (Premier), plus open Voxtral Mini Transcribe Realtime and Voxtral Small under Apache 2.0.
• Code: Codestral (v25.08, Premier) for code completion, and Codestral Embed (v25.05) for code retrieval.
• Embeddings and moderation: Mistral Embed (Premier), Mistral Moderation 2 with a 128K window and jailbreak detection, and Shieldstral 1.0 under Apache 2.0.
• Forecasting: Timestral 1.0 in 4 sizes (5M, 28M, 123M, 209M parameters) under modified MIT.

A Facebook post dated October 2026 reports that Voxtral 3 launched on October 20, 2026, with 50+ languages for transcription. Its author notes the benchmarks are Mistral’s own and unverified.

How Much Does Mistral Cost?

Mistral’s consumer plans run from Free to $24.99 per user per month, and its API lists Mistral Large at $0.50 per million input tokens and $1.50 per million output tokens. The pricing page does not name the Large version for that API rate, so confirm which model it covers.

Plan	Price	What it adds
Free	$0	Limited messages, searches, and coding sessions; 100+ connectors
Pro	$14.99/mo	More messages, faster responses, all-day coding, spreadsheet and slide generation
Team	$24.99/user/mo	Higher limits, up to 30GB storage per user, data export
Enterprise	Contact sales	Private deployments, audit logs, SAML SSO

Verified students get Pro for $5.99 per month. Batch processing cuts API prices by 50%, and cached input tokens cut input cost by up to 90%.

Mistral Large 4 preview pricing of $1.36 input and $4.18 output costs about 2.7 times the listed Large rate on input. For other vendors’ costs, read our AI chatbot pricing comparison.

Which Mistral Model Should You Use?

Use Small 4 by default, Medium 3.5 for coding agents, Large 4 for frontier tasks once weights land, and Ministral 3 for small hardware. The branches below tie each pick to a published license or spec.

Choose Small 4 if:
– You want Apache 2.0 terms with reasoning and coding in one model.
– You are starting a new project and want the lowest legal friction.

Choose Medium 3.5 if:
– You build coding or agentic workflows and want frontier-class capability below Large.
– You accept the modified MIT license after reading it.

Choose Large 4 if:
– You need the strongest Mistral model and can test the preview API at $1.36 and $4.18 per million tokens.
– You can wait for the open weights promised by the end of October 2026.

Choose Ministral 3 if:
– You run text and vision locally on 3B, 8B, or 14B models.

What Do Reddit and Facebook Users Say About Mistral?

Mistral threads focus on the Large 4 open-weights date and on whether more releases are coming. On r/LocalLLaMA, “Europe rejoins the fight with Chonky! Mistral Large 4 Released, Open weights end of month, who’s ready?” drew 525 upvotes and 126 comments.

A separate thread, “Does anyone know if any new releases from Mistral are planned?”, drew 728 upvotes and 333 comments. Facebook posts about Mistral are mostly news reposts on Large 4, Voxtral 3, and Timestral, with near-zero engagement.

These are thread titles, not verified findings. For how Mistral stacks up against Meta, see our LLaMA vs Mistral comparison.

Frequently Asked Questions (FAQ)

What is the newest Mistral model?

Mistral Large 4 (v26.10) is the newest, in public preview since October 6, 2026. Mistral Medium 3.5 (v26.04) and Small 4 (v26.03) are the newest in their tiers.

Is Mistral open source?

Several Mistral models ship open weights under Apache 2.0 (Small 4, Large 3, Ministral 3) or modified MIT (Medium 3.5). Premier models such as Codestral and the OCR line use a commercial license.

What is the difference between Mistral Large, Medium, and Small?

Large is the frontier tier, Medium is a frontier-class agentic and coding model, and Small is a compact model that combines instruct, reasoning, and coding. Small 4 uses Apache 2.0, and Medium 3.5 uses modified MIT.

How much does Mistral Large 4 cost?

Mistral lists $1.36 per million input tokens and $4.18 per million output tokens for the Large 4 preview API.

Is Mistral better than ChatGPT?

Mistral offers lower API prices and open-weight options, while ChatGPT offers a broader consumer product. Compare them in our ChatGPT vs Mistral article.

Does Mistral have a free plan?

Yes, Mistral’s Free plan includes limited messages, web searches, and coding sessions, plus 100+ connectors. Pro costs $14.99 per month.

Where can I find Mistral alternatives?

Browse our Mistral Alternatives roundup for comparable models.

Final Verdict

Mistral Small 4 is the best default for most teams, Medium 3.5 is the pick for coding agents, and Large 4 is the one to watch once its open weights ship. The Apache 2.0 license on Small 4 and Ministral 3 is the strongest legal position among the major open-weight families.

Confirm every figure on Mistral’s pricing page and the Mistral docs before you budget, since Large 4 terms were still unpublished in October 2026. For the bigger picture on licenses and costs, read Open Source vs Closed Source LLMs. For wider comparisons, see the best AI models hub or the AI Comparison homepage.