Devstral Small 1.1
Up to 30%Deprecated 31 May 2026Call Devstral Small 1.1 through LLM.API when you want Mistral-family text generation with unified auth, provider choice, and production-friendly defaults.
What is Devstral Small 1.1?
On LLM.API, Devstral Small 1.1 (devstral-small-2507) serves as a Mistral conversational model for products that need 131K tokens context windows and predictable token pricing. devstral-small-2507 provided by mistral. It is wired for API access through LLM.API with OpenAI-compatible patterns.
Providers
LLM.API routes Devstral Small 1.1 to the providers below, with discounted effective rates versus list price.
List price by provider ($ / 1M tokens)
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| in $100; out $300 per 1M tokens | 131K tokens | tools, streaming, JSON, structured |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.
Try this model
Test Devstral Small 1.1 right here — free to start.
Suggestions for your first prompt
Code snippet
Call Devstral Small 1.1 through the OpenAI-compatible API — POST /v1/chat/completions.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAP_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="devstral-small-2507",
messages=[
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."},
],
)
print(resp.choices[0].message.content){
"model": "devstral-small-2507",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}5 Core Capabilities
Code assistance
Helps write, explain, refactor, and debug application code across common languages. Relevant for `devstral-small-2507` workloads on LLM.API.
Long-context synthesis
Summarizes and cross-references information across large prompts when context allows. Grounded in the model's chat role rather than generic chat claims.
Multilingual drafting
Drafts and translates professional content across major business languages. Relevant for `devstral-small-2507` workloads on LLM.API.
Conversational UX
Maintains coherent multi-turn assistant behavior for product chat surfaces.
Structured outputs
Can produce JSON-friendly or schema-oriented responses when prompted carefully. Relevant for `devstral-small-2507` workloads on LLM.API.
6 Most Valuable Use Cases
- Multilingual localization drafts for UX copy with Devstral Small 1.1
- Internal knowledge assistants grounded with your retrieval layer
- Meeting-note cleanup and action-item generation with Devstral Small 1.1
- Customer support copilots that draft accurate, on-brand replies
- Sales and success email drafting with CRM context with Devstral Small 1.1
- Data extraction into JSON for downstream systems
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Intelligent AI Routing
Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.
One endpoint, every model. -
Cost-Aware Execution
Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.
More performance, less spend. -
Resilient Fallback Flows
Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.
Never go dark on users. -
Deep LLM Observability
Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.
See every token, everywhere. -
Task-Level Orchestration
Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.
Think tasks, not models. -
High-Throughput Batch APIs
Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.
Scale from 1 to millions.
Why run Devstral Small 1.1 on LLM.API?
Unified AI Routing
Practical: Reach Devstral Small 1.1 and sibling models through one OpenAI-compatible endpoint.
Cost Control
Compare provider price points and keep spend visible as you scale Devstral Small 1.1.
Reliability Layer
Retry and route across configured providers when a single upstream blips.
Observability
Trace prompts, tokens, and errors for Devstral Small 1.1 alongside the rest of your stack.
Drop-in SDKs
Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Model Breadth
Swap Devstral Small 1.1 for chat, media, or embedding alternatives without rewriting auth.
When to Use — When NOT to Use
Use it if...
- Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Devstral Small 1.1)
- You need a general-purpose text model for assistants, agents, or content workflows (Devstral Small 1.1)
- You want OpenAI-compatible chat completions through a single LLM.API key (Devstral Small 1.1)
- You need provider failover options exposed for this model id (Devstral Small 1.1)
Avoid if...
- You require on-prem only deployment with no cloud inference
- Your use case depends on unpublished proprietary benchmarks not listed here
- You need pure embedding, OCR, or media generation instead of chat
- You need guaranteed real-time hard latency SLAs without benchmarking the provider
COMMUNITY
What developers say about Mistral models
Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Devstral Small 1.1.
- Long-form paid reviews rate Mistral Large around 4/5 and call it the best European-hosted option when data residency matters.
- For pure coding, community consensus is that it trails the top US and Chinese models, though it is considered fully usable as an assistant.
- Developers pick it mainly for EU hosting, predictable pricing, and open-weight siblings rather than leaderboard position.
SOURCES
Frequently Asked Questions
Where is the canonical page for Devstral Small 1.1?
https://llmapi.ai/models/mistralai-devstral-small-2507/
What is Devstral Small 1.1?
devstral-small-2507 provided by mistral. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `devstral-small-2507`.
When should I choose Devstral Small 1.1?
You need provider failover options exposed for this model id — especially when you specifically need Devstral Small 1.1.
Can I use tools or structured outputs with Devstral Small 1.1?
Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.
Does Devstral Small 1.1 support streaming?
Yes—at least one listed provider advertises streaming.
How do I call Devstral Small 1.1 via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "devstral-small-2507" and your LLM.API key. See the code snippet on this page.
Which providers serve Devstral Small 1.1?
LLM.API currently lists: mistral. Availability can vary by region and account.
Is Devstral Small 1.1 a chat model?
Yes—Devstral Small 1.1 is exposed as a chat/completions-style endpoint on LLM.API.
What modalities does Devstral Small 1.1 support?
Devstral Small 1.1 accepts text and produces text according to its architecture metadata on LLM.API.
What is the context length for Devstral Small 1.1?
Reported context for Devstral Small 1.1 is 131K tokens. Always verify the active provider row if multiple providers are listed.
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