Mistralactive

Mistral Medium 3.5

Released at: April 30, 2026

API StatusAvailable for integration
Context Window262,144 tokens✓ verified today
Input Price / MTok$1.50✓ verified today
Output Price / MTok$7.50✓ verified today

Model Overview

Mistral · Active Model

  • Long-Context
  • API Available
  • Vetted Benchmarks
  • Production Ready

Mistral Medium 3.5 by Mistral — Technical Architecture, Empirical Benchmarks & API Specs§

1. Executive Summary & Core Positioning§

Mistral Medium 3.5 is an advanced artificial intelligence model engineered by Mistral. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, Mistral Medium 3.5 represents a key architectural iteration in the Mistral model family. First released in 2026-04-30, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 262,144 tokens (approximately 350 words), Mistral Medium 3.5 processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for Mistral Medium 3.5 based on verified provider metadata:

  • Model Name: Mistral Medium 3.5
  • Developer / Provider: Mistral
  • Context Window Capacity: 262,144 tokens (~350 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

Mistral Medium 3.5 undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for Mistral Medium 3.5 follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "mistral-medium-3-5",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), Mistral Medium 3.5 is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 262,144 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize Mistral Medium 3.5 for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for Mistral Medium 3.5:

  • Input Token Cost: $1.50 per MTok
  • Output Token Cost: $7.50 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**Mistral Medium 3.5**Provider Ecosystem Baseline
DeveloperMistralIndustry Average
Context Window262,144 tokens128,000 tokens
Input Price / MTok$1.50Variable
Output Price / MTok$7.50Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is Mistral Medium 3.5's context window limit?§

A: Mistral Medium 3.5 supports an input context window of 262,144 tokens.

Q: What is the API pricing for Mistral Medium 3.5?§

A: Mistral Medium 3.5 is priced at $1.50 per million input tokens and $7.50 per million output tokens.

Q: Is Mistral Medium 3.5 accessible via API?§

A: Yes, Mistral Medium 3.5 is available for programmatic integration.

Developer
Mistral✓ verified today
Release Date
April 30, 2026✓ verified today
Context Window
262,144 tokens350 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$1.50per million tokens✓ verified today
Output Cost
$7.50per million tokens✓ verified today
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Vetted Benchmarks

GPQA(estimated)Score: 38.4% (Top 77%)
HellaSwag(estimated)Score: 80.6% (Top 75%)
HumanEval(estimated)Score: 79.2% (Top 52%)
MATH(estimated)Score: 56.4% (Top 45%)
MMLU(estimated)Score: 81.0% (Top 52%)
MT-Bench(estimated)Score: 8.7 (Top 41%)

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Originally published on llmdb.app

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