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Models / Mistral / Ministral 3 8B 2512

Ministral 3 8B 2512 APIOPEN WEIGHTS262K context

by Mistral · text+image->text · released 2025-12-02

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.15
Output / 1M
$0.15
Context
262K
Providers
2
HF downloads · 30d
101.4K
Cheaper than
92% of catalog

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Ministral 3 8B 2512?

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

Ministral 3 8B 2512 on the release timeline

$0.10$0.14$0.20Ministral 3 8B 2512 · $0.152025-122025-122025-12
Each point is a ministral release, placed at its launch date with its current output price (log scale, $/1M). Bubble size ∝ context window; Ministral 3 8B 2512 is highlighted. Source: provider catalog, verified July 2026.

Ministral 3 8B 2512 pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

ModelInput / 1MOutput / 1MCache readCache writeContext
Ministral 3 8B 2512$0.15$0.15$0.01262K

On output price, Ministral 3 8B 2512 is cheaper than 92% of the 309 models in the catalog. It is served by 2 providers; the best combined rate at our last snapshot was ≈ $0.15 / $0.15 per 1M via Mistral, with upstream quantizations fp8.

What Ministral 3 8B 2512 costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$7.80
RAG / knowledge base200M / 20M$33.00
Coding agent80M / 25M$15.75
Batch extraction150M / 8M$23.70
Content generation20M / 40M$9.00

Estimate your own monthly cost

= input × $0.15 + output × $0.15 per 1M · pay-as-you-go, computed in your browser.

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Ministral 3 8B 2512 vs alternatives

Pick Ministral 3 8B 2512 when you want open weights you can also self-host. If price is the only priority, Ministral 3 3B 2512 is cheaper per token.
ModelInput / 1MOutput / 1MContextOur test
Ministral 3 8B 2512$0.15$0.15262K
Ministral 3 14B 2512$0.20$0.20262K
Mistral Small 3.2 24B$0.07$0.20128K
Ministral 3 3B 2512$0.10$0.10131K
Trinity Mini$0.04$0.15131K
Command R7B (12-2024)$0.04$0.15128K

Specs

Model IDmistralai/ministral-8b-2512
Modalitytext+image->text (input: text, image)
Context window262,144 tokens
Tool / function calling✅ Yes
Structured output (JSON)✅ Yes
Released2025-12-02
Open weightsmistralai/Ministral-3-8B-Instruct-2512 · 101.4K downloads / 179 likes (30d)

How to call Ministral 3 8B 2512

from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="mistralai/ministral-8b-2512",
    messages=[{"role": "user", "content": "Hello"}],
    # supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)
curl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mistralai/ministral-8b-2512","messages":[{"role":"user","content":"Hello"}]}'
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "mistralai/ministral-8b-2512",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Ministral 3 8B 2512 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Ministral 3 8B 2512

Tips are derived from Ministral 3 8B 2512's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Ministral 3 8B 2512

Popular open-source projects for running and building with Ministral 3 8B 2512 — star counts pulled from GitHub (July 2026).

ollama/ollama★ 175.3K
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Go
langgenius/dify★ 147.5K
Production-ready platform for agentic workflow development.
TypeScript
open-webui/open-webui★ 144.0K
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Python
langchain-ai/langchain★ 140.8K
The agent engineering platform.
Python
ggml-org/llama.cpp★ 119.1K
LLM inference in C/C++
C++
vllm-project/vllm★ 85.2K
A high-throughput and memory-efficient inference and serving engine for LLMs
Python

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Ministral 3 8B 2512

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → mistralai/ministral-8b-2512. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Ministral 3 8B 2512 ships open weights (mistralai/Ministral-3-8B-Instruct-2512, ~101.4K downloads and 179 likes in the last 30 days), with community quantizations (fp8) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 2 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff; because Ministral 3 8B 2512 is served by 2 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

Best Open Source LLMs
DataLLM Lab Blog
How OpenAI-Compatible APIs Work
DataLLM Lab Blog
We Benchmarked LLM Coding Cost & Quality
DataLLM Lab Blog

Call Ministral 3 8B 2512 with one key

300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.

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Frequently asked questions

What is Ministral 3 8B 2512?

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities. It accepts text, image input with a 262K-token context window and was released on 2025-12-02. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Ministral 3 8B 2512 cost?

On DataLLM Lab it is $0.15 per 1M input tokens and $0.15 per 1M output tokens, with cached input at $0.01/1M — cheaper than about 92% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Ministral 3 8B 2512?

262K tokens.

Is Ministral 3 8B 2512 open source?

Yes — open weights are published on Hugging Face (mistralai/Ministral-3-8B-Instruct-2512), with about 101.4K downloads and 179 likes in the last 30 days. You can self-host it or call it via DataLLM Lab.

How do I call the Ministral 3 8B 2512 API?

Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "mistralai/ministral-8b-2512". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.

What are good alternatives to Ministral 3 8B 2512?

Close options by price and capability include Ministral 3 14B 2512, Mistral Small 3.2 24B, Ministral 3 3B 2512 — all callable with the same DataLLM Lab key.