Atlas / Models / Mistral AI / Mistral: Devstral Small 1.1

Mistral: Devstral Small 1.1✓ Catalog verified

mistralai/devstral-small

Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it features a 128k token context window and supports both Mistral-style function calling and XML output formats. Designed for agentic coding workflows, Devstral Small 1.1 is optimized for tasks such as codebase exploration, multi-file edits, and integration into autonomous development agents like OpenHands and Cline. It achieves 53.6% on SWE-Bench Verified, surpassing all other open models on this benchmark, while remaining lightweight enough to run on a single 4090 GPU or Apple silicon machine. The model uses a Tekken tokenizer with a 131k vocabulary and is deployable via vLLM, Transformers, Ollama, LM Studio, and other OpenAI-compatible runtimes.

Input price
$0.10 /1M
Output price
$0.30 /1M
Context
131K
Modalities
text
Released
Jul 10, 2025
Tool calling
✓ Yes
Atlas signal
84/100
01

Overview

Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it features a 128k token context window and supports both Mistral-style function calling and XML output formats. Designed for agentic coding workflows, Devstral Small 1.1 is optimized for tasks such as codebase exploration, multi-file edits, and integration into autonomous development agents like OpenHands and Cline. It achieves 53.6% on SWE-Bench Verified, surpassing all other open models on this benchmark, while remaining lightweight enough to run on a single 4090 GPU or Apple silicon machine. The model uses a Tekken tokenizer with a 131k vocabulary and is deployable via vLLM, Transformers, Ollama, LM Studio, and other OpenAI-compatible runtimes.

Access: available through the official Mistral AI API. Context window: 131K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifiermistralai/devstral-small
ProviderMistral AI
Model typeText LLM
Context window131K catalog
Input modalitiestext
Output modalitiestext
ReleasedJul 10, 2025
TokenizerMistral
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltymax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_p
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "temperature": 0.3
}
03

Pricing

Live pricing components for mistralai/devstral-small as published in the catalog.

$0.10
Input /1M
$0.30
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$1e-7$0.10 / 1MPer input token
Completion tokens$3e-7$0.30 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.11Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-Hosting✓ SupportedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

Mistral: Devstral Small 1.1
MMLU Signal (Reasoning)
79signal
Coding Signal (HumanEval proxy)
97signal
Math Signal (GSM8K proxy)
79signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call Mistral: Devstral Small 1.1 through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="mistralai/devstral-small",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does Mistral: Devstral Small 1.1 cost?

$0.10 per 1M input tokens and $0.30 per 1M output tokens on the official Mistral AI API.

What is the context window of Mistral: Devstral Small 1.1?

Mistral: Devstral Small 1.1 supports up to 131K tokens of context.

Does Mistral: Devstral Small 1.1 support tool / function calling?

Yes, Mistral: Devstral Small 1.1 supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access Mistral: Devstral Small 1.1?

Use the official Mistral AI API with the model id `mistralai/devstral-small`. See the Quick start section above for code examples.