Mistral Small 3
Mistral AI · released Jan 28, 2025 · mistralai/Mistral-Small-24B-Instruct-2501
- Type
- Open weightsApache License 2.0
- Params
- 23.6B
- Context
- 33K
about 25K words of context
Our take
Written Aug 3, 2026Mistral Small 3 is a 23.6-billion-parameter text model released in early 2025 with a permissive Apache licence. Its standout measured skill is coding, and it is positioned as a budget-friendly workhorse for teams who need open weights with commercial freedom.
Pick this for coding assistance where its Arena score is strongest, or for budget-conscious text generation with a permissive licence that allows commercial use and redistribution. Use it for self-hosted deployments where you need open weights without usage restrictions. Skip it if you need creative writing, image or video support, or guaranteed throughput data on every host.
The case for it
- Strongest measured skill is coding, with an Arena Coding score 37 points above its overall text score.
- Permissive Apache 2.0 licence allows commercial use, modification and redistribution.
- Lowest-in-class pricing for open weights at this parameter scale across all tracked offers.
- Coding lead over creative writing is substantial, with an 85-point gap between its highest and lowest reported Arena skills.
The case against it
- Creative writing is a clear relative weakness, scoring 47 points below its overall text score and the lowest of all six reported Arena skills.
- No measured throughput for two-thirds of offers; only one of three hosts lists a speed figure.
- Dense architecture means all 23.6 billion parameters are active per token, with no disclosed efficiency figure to suggest otherwise.
How good is it?
IntelligencePuzzles, maths, exam questions
Arena Text (overall)131st of 143 · 1274.2
CodingWriting and fixing code on its own
Arena Coding128th of 143 · 1312.4
Arena Coding is the only board that has scored it for this.
AgenticPlanning, calling tools, staying on task
Nobody we watch has scored Mistral Small 3 for this. We would take the rating from Arena Agent (IPS).
WritingWe do not rate this
Two boards come close and neither tests writing: Arena Creative Writing asks people which of two replies they prefer, and LiveBench Language tests whether a model understood a passage. So we show where Mistral Small 3 placed and give it no mark out of five.
These tests check whether a model follows instructions — a precondition for all the work above, but not a measure of how well that work is done, which is why they get no rating.
Every published score for this model6 scoresEvery figure we hold, from 6 boards, with who ran it and a link to the source — including the boards no rating above is built on.
Can you run it yourself?
- Fits in memory
- weights load entirely on the card
- Spills to system RAM
- some weights offload; much slower
- Too large
- will not load even with offload
- est
- size is calculated; the verdict could change by 10%
Comfortable fit
GeForce RTX 4090 · 24 GB
Room to spare. 5.9 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 13.9 GB spare means a 10% error in the size would not change the answer.
Apple M2 (10-core GPU) · 24 GB
Borderline fit on an estimated size. It leaves 1.1 GB spare on a size we calculated rather than measured, and a 10% error either way would change the answer.
Memory use by level
Against a 24 GB card.
All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.
Check against your own machine → · All 71 devices, with every size →
Or rent it from someone else
Cheapest of 3 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.
- per 1M tokens
- $0.050 in / $0.080 out
- Context served
- 33K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| OpenRouter | $0.050 / $0.080 | 33K | not measured | Unknown | Unknown | Unknown |
| DeepInfrafp8 | $0.050 / $0.080 | 33K | not measured | Unknown | Unknown | Unknown |
| DeepInfrafp8 | $0.050 / $0.080 | 33K | 53 tok/s | No | No | Confirmed |
DeepInfraAcross the 3 listings we hold: 1 say they do not train on prompts, 0 say they do and 2 do not say. 1 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.
What each host's API supports
From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.
- ✓
- Supported
- ✗
- Not supported
- Not published
- host gave no parameter list
| Provider | Tool calling | JSON output | Strict schema |
|---|---|---|---|
| OpenRouter | ✗ | ✓ | ✓ |
| DeepInfrafp8 | |||
| DeepInfrafp8 | ✗ | ✓ | ✓ |
Tool calling: 0 of 3 listings say yes, 2 say no, 1 publishes no parameter list. JSON output: 2 of 3 listings say yes, 1 publishes no parameter list. Strict schema: 2 of 3 listings say yes, 1 publishes no parameter list.
Models people weigh against Mistral Small 3
When we formed this view
Dates behind this page
Prices last checked 4d ago
What we do not know about this model yet
- We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
- 1 of 3 listings publish no parameter list, so what their API accepts is unknown to us.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 2 of 3 listings do not say whether they train on prompts.
- We hold no cached-input rate for any of its listings.
Licence and identifiers
What the licence allowsApache License 2.0, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.
Licence
Apache License 2.0
Fully permissive: commercial use, redistribution, and derivatives allowed. Requires attribution and a copy of the license. Includes an express patent grant.
Identifiers
- Hugging Face
- mistralai/Mistral-Small-24B-Instruct-2501
- Architecture
- Dense
- Modality record
- text->text
- Catalogue slug
- mistralai-mistral-small-3