Railwail
Prijava

Codestral

KodaNi razpoložljivo
od Mistral AIID modela: codestral

Mistral's code-specialized model. Optimized for code generation, completion, and understanding across 80+ languages.

Poglej alternativePrimerjaj
Stanje
Ni razpoložljivo
Kontekst
256.000 žetonov
Največji izhod
8192 žetonov
Vhod → Izhod
Besedilo → Besedilo
Razvijalec
Mistral AI
Posodobljeno
23. september 2026

Codestral trenutno ni na voljo

Podrobnosti na tej strani si lahko še vedno prebereš. Z eno od razpoložljivih alternativ spodaj lahko takoj zaženeš primerljiv model.

Na alternative
01

Primerljivi modeli

Vsi v tej kategoriji
02

Igrišče

Preizkusi Codestral

Klepet

Trenutno ni razpoložljivo

Trenutno ni na voljo.

Igrišče je onemogočeno. Primerljive modele najdeš v isti kategoriji: Oglejte si alternative

Preizkusi Codestral

Pošlji sporočilo. Odgovor pride v celoti, ko je model končan (brez pretakanja).

Sistemski poziv
Maks. dolžina odgovora (tokeni)

Ta zagon

Brez cene – trenutno ni na voljo.

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03

O Codestral

PovzetekOd 23. september 2026

Codestral je model razvijalca Mistral AI iz kategorije Koda. Codestral trenutno ni dostopen na Railwail. Kontekstno okno vsebuje 256.000 žetonov, odgovor pa je lahko dolg do 8192 žetonov.

Ozadje

O Mistral AI

Ustanovljeno 2023 · Paris, France

Mistral AI was founded in April 2023 in Paris by Arthur Mensch (CEO, former DeepMind), Guillaume Lample and Timothée Lacroix (both former Meta FAIR co-authors of the LLaMA papers). Mistral has built a frontier-scale European LLM lab with a portfolio mixing fully open-weight releases (Mistral 7B, Mixtral 8x7B, Mixtral 8x22B, Mistral Small) and commercial closed-API models (Mistral Large, Mistral Embed, Mistral Saba). The company has raised over €1B from investors including Andreessen Horowitz, General Catalyst, Lightspeed, Salesforce, Nvidia and Microsoft, with a 2024 valuation around €6B. Codestral was released May 2024 as Mistral's first dedicated code model — a 22B dense transformer trained on 80+ programming languages with native fill-in-the-middle support for IDE integrations. A successor, Codestral 25.01, followed in January 2025.

Obiščite Mistral AI

Arhitektura

Decoder-only Transformer for code (Mistral architecture)

Codestral-22B is a 22B dense decoder-only transformer using Mistral's standard architecture: 56 layers, 6,144 hidden size, 48-head grouped-query attention with 8 KV heads, sliding-window attention (4,096-token window), RoPE positional embeddings with theta=1M (for long-context support), SwiGLU activations and RMSNorm. The tokeniser is the Mistral BPE with 32,768 entries plus added fill-in-the-middle special tokens (`[PREFIX]`, `[SUFFIX]`, `[MIDDLE]`). Training combined a standard left-to-right autoregressive objective with FIM training for IDE-grade code completion. The training corpus covers 80+ programming languages drawn from public code repositories, plus natural-language code documentation pairs and instruction data for the chat / explain capability. Released May 2024 under the Mistral AI Non-Production License (MNPL), which permits open-weights research and evaluation but not commercial production use without a separate license or hosted API access.

Parametri
22B (dense)
Kontekst
32.000 žetonov

Zmožnosti

  • 22B dense transformer purpose-built for code
  • Native fill-in-the-middle (FIM) for IDE autocomplete
  • Trained on 80+ programming languages
  • 32K context window
  • Competitive with CodeLlama-34B and DeepSeek-Coder-33B at smaller size
  • Strong on mainstream: Python, JS/TS, Java, C/C++, Go, Rust, Bash, SQL, PHP, Swift
  • Open weights available under MNPL (research only)
  • Best for: IDE code completion, code generation, explanation and refactoring across mainstream languages.

Usposabljanje in licenca

Trained on trillions of tokens (exact figure not disclosed) of public code repositories across 80+ programming languages, natural-language code-documentation pairs, and instruction-style code data for chat and explain capabilities. Knowledge cutoff approximately early 2024. Training combined autoregressive and fill-in-the-middle objectives.

Licenca: Mistral AI Non-Production License (MNPL). Open weights for research, evaluation and personal use; commercial production requires Mistral commercial license or hosted API access (la Plateforme, AWS Bedrock, Azure AI Studio).

Preizkusi varnosti: Mistral publishes a model card for Codestral. Safety focus is on code-specific risks (malware, vulnerability generation) rather than general consumer-chat alignment.

Znane omejitve

  • MNPL blocks commercial production use of open weights
  • Smaller than successor Codestral 25.01 and below DeepSeek-Coder V2 on top benchmarks
  • 32K context shorter than newer code models (DeepSeek-Coder V2: 128K)
  • Weaker on rare languages and DSLs
  • Not as strong on agentic / repo-level reasoning as longer-context code models
  • No multimodal input (no image-of-code understanding)

Raziskovalni članki

04

Cene

Trenutno ni na voljo. Za ta model trenutno ni cene, zato ga ni mogoče zagnati.

05

API

Pokličite Codestral s svojim Railwail API ključem. V zahtevku uporabite to ID modela:
codestralDokumentacija APIPridobite API ključ

Trenutno ni dostopno

Model nima preverljive cene ali je deaktiviran; klici API so zavrnjeni.

06

Specifikacije

ID modela
codestral
Razvijalec
Mistral AI
Kategorija
Koda
Vhod
Besedilo
Izhod
Besedilo
Kontekstno okno
256.000 žetonov
Maks. izhod
8192 žetonov
Velikost modela
22B (dense)
Licenca
Mistral AI Non-Production License (MNPL). Open weights for research, evaluation and personal use; commercial production requires Mistral commercial license or hosted API access (la Plateforme, AWS Bedrock, Azure AI Studio).
Kataložni vnos posodobljen
23. september 2026

Oznake

  • coding
  • fast
  • multilanguage
07

Primeri pozivov

Primeri iz kataloga Railwail. Niso bili generirani v živo na tej strani.

  • TypeScript API Handler

    Write a type-safe Express middleware for JWT authentication in TypeScript
    Prikaži primer odgovora

    import { Request, Response, NextFunction } from 'express'; import jwt from 'jsonwebtoken'; interface JwtPayload { userId: string; email: string; role: 'admin' | 'user'; } declare global { namespace Express { interface Request { user?: JwtPayload; } } } export const authenticate = ( req: Request, res: Response, next: NextFunction ): void => { const token = req.headers.authorization?.split(' ')[1]; if (!token) { res.status(401).json({ error: 'No token provided' }); return; } try { const decoded = jwt.verify( token, process.env.JWT_SECRET! ) as JwtPayload; req.user = decoded; next(); } catch (err) { res.status(403).json({ error: 'Invalid or expired token' }); } };

  • Rust Error Handling

    Write a Rust function that reads a JSON config file and returns a parsed struct with proper error handling
    Prikaži primer odgovora

    use serde::Deserialize; use std::fs; use std::path::Path; use thiserror::Error; #[derive(Debug, Deserialize)] pub struct AppConfig { pub host: String, pub port: u16, pub database_url: String, pub max_connections: Option<u32>, } #[derive(Error, Debug)] pub enum ConfigError { #[error("Failed to read config file: {0}")] IoError(#[from] std::io::Error), #[error("Failed to parse config JSON: {0}")] ParseError(#[from] serde_json::Error), #[error("Config file not found: {0}")] NotFound(String), } pub fn load_config(path: &str) -> Result<AppConfig, ConfigError> { if !Path::new(path).exists() { return Err(ConfigError::NotFound(path.to_string())); } let contents = fs::read_to_string(path)?; let config: AppConfig = serde_json::from_str(&contents)?; Ok(config) } // Usage: // let config = load_config("config.json")?;

08

Primeri uporabe

Kaj se uporablja za

  • IDE code completion (continue.dev, JetBrains)
  • Code generation and refactoring
  • Code explanation and review
  • Cross-language code translation
  • Self-hosted developer assistants (research)
  • Production deployments via Mistral hosted API
09

Pogosta vprašanja

Kaj je Codestral?

Codestral je model podjetja Mistral AI iz kategorije Koda. Naveden je na Railwailu, vendar ga trenutno ni mogoče zagnati.

Koliko stane Codestral na Railwailu?

Codestral se trenutno ne more zagnati na Railwailu, zato ni trenutne cene. Razpoložljive alternative s cenami so navedene spodaj na tej strani.

Kako veliko je kontekstno okno Codestral?

Kontekstno okno Codestral vsebuje 256.000 žetonov. Odgovor je lahko dolg do 8192 žetonov.

Kako hiter je Codestral?

Za Codestral je na Railwailu še premalo izmerjenih zagonov, da bi navedli čas izvajanja. Odvisno je od vnosa, nastavitev in obremenitve pri ponudniku.

Je Codestral boljši od Code Llama 13B Instruct?

To je odvisno od naloge. Codestral (Mistral AI) in Code Llama 13B Instruct (Meta) sta oba modela iz kategorije Koda. Stran za primerjavo prikazuje njune cene in specifikacije drug ob drugem.

Primerjaj Codestral in Code Llama 13B Instruct

Ali lahko Codestral uporabljam zdaj?

Trenutno ni na voljo. Stran ostane na spletu; razpoložljive alternative iz iste kategorije so navedene spodaj.

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