Magistral Small

Retired Jul 2026

A 24B open-weight reasoning model from Mistral AI under Apache 2.0, released June 2025, with traceable chain-of-thought.

Params: 24B
Context: 128K tokens
Max output: 33K
Released: Jun 2025
License: Apache 2.0

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Hosted API pricing

How we price

Order

Providers are listed cheapest input rate first, then by output rate, a tie going to the creator's own listing. A provider that lists the model without a published rate sits at the end.

Prices

Base-tier, on-demand rates in USD per 1M tokens, converted at ECB reference rates where a provider publishes in another currency. Cached-input and batch rates show only where a provider publishes them. "Cheapest" marks the one provider with the lowest input and output pair; a tie wears no badge.

Cost

Input rate times the input tokens plus output rate times the output tokens, at the monthly volume set above the table. Cached-input, batch, long-context and reasoning-token billing are not modelled.

Transparency and funding

Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.

Every provider serving Magistral Small, cheapest input first. Set your monthly volume to see what each would bill.

Input M Output M

Every provider serving Magistral Small, with its price per 1M input and output tokens and what the volume above would cost
Provider	Input /1M	Output /1M	Cost at 10M in + 2M out	Link
Mistral Creator	Open weights, no hosted price			Visit website

Heads up: Base-tier, on-demand rates per 1M tokens; cached, batch and long-context tiers excluded. A provider may serve a shorter context or a quantized build than the creator's release. Verify before provisioning. More on how we price.

Estimated cost to self-host

Magistral Small needs about 20 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 2× RTX 3060 at about $115 a month.

Single node ≤ 8

What it costs to self-host Magistral Small at each precision: the memory it needs, the cheapest rental that holds it, that rental's month and the API volume it pays off at
Precision	Memory	Cheapest fit (32K context)(Full 128K context)	Cost /mo
4-bit INT4 / FP4	20 GB26 GB	2× RTX 3060	$115$187
8-bit FP8 / INT8	29 GB37 GB	2× RTX 4060 Ti	$187$374
16-bit FP16 / BF16	55 GB71 GB	4× RTX 4060 Ti	$374$461

Estimates based on median on-demand rates for Nvidia GPUs. Memory is weights plus KV cache for one request, using FP8 KV cache where supported and FP16/BF16 otherwise. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.

Thunder Compute

RTX A6000 from $0.35, A100 from $1.09, per GPU per hour

Billed per minute, no commitment, no minimums

One click into VS Code or Cursor, no SSH setup

See live pricing

Capabilities

What Magistral Small accepts and can do, as published by Mistral.

Text Accepts and generates natural-language text.
Image Accepts images as input alongside text.
Reasoning Thinks before it answers, always on or as a switchable mode.
Function calling Connect to external tools, APIs, and systems.
Structured output Return responses in structured formats like JSON.

Common questions

What is Magistral Small good for?

Self-hosted reasoning with a traceable chain of thought, taking text and images. Apache 2.0 weights, small enough for a single consumer GPU.

When is Magistral Small not a good fit?

Hosted use: Mistral retired it from its API in July 2026, which leaves self-hosting. Its maximum output limits long reasoning traces in one response.

What is the cheapest way to run Magistral Small?

No provider we track hosts it; self-hosting on the cheapest rental that fits (2x RTX 3060, $0.16 per hour) costs about $115 a month.

Can I self-host Magistral Small?

Yes. The weights are Apache 2.0 licensed. At 4-bit it needs about 20 GB of GPU memory, which starts at roughly $115 a month on the cheapest rental that fits.