Mistral: Devstral 2 2512

Public pricingIntelligence 79/100Large memory工具调用

Mistral: Devstral 2 2512 是一款文本模型,适合编码、软件工程和智能体工作流。它结合了强大的编码能力、可靠的工具调用与智能体表现、262K tokens上下文和均衡成本定位,可在编码、软件工程和智能体工作流中提供可靠表现。它适合重视质量、速度与成本的团队,能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$0.40/1M

Output

$2.00/1M

Cached

$0.04/1M

Batch

$0.15/1M

Calculate your Devstral 2 2512 bill.

Set your workload — see cost at your exact volume.

What would Devstral 2 2512 cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

Devstral 2 2512 at a glance.

Memory

262,144

tokens

Max reply

32,768

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

mistral

Released

Dec 2025

Training cutoff

Jul 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • swe_bench_verified

    72.2

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Devstral 2 2512

  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

FAQ

Devstral 2 2512 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Devstral 2 2512 costs roughly $110 per month. Input is $0.40 /1M tokens and output is $2.00 /1M tokens.
Devstral 2 2512 has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Beyond text generation, Devstral 2 2512 supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Devstral 2 2512 was released in December 2025, with training data cut off around July 2025.
Models in a similar class include Codestral 2508, Mistral Large 3 2512, Ministral 3 14B 2512. The "Similar models" section below this FAQ links into each.

Still unsure?

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