Magistral Medium latest

Mistral AI chat

Magistral Medium latest is a Mistral AI chat model.It supports a 262,144-token context windowwith up to 262,144 output tokens.Input is priced at $1.50/M tokens and output at $7.50/M tokens. Capabilities include function calling, vision, reasoning. Route Magistral Medium latest via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Oct 22, 2026 View source ↗
Cost calculator

Estimate Magistral Medium latest spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
0262,144
400
0200,000
5,000
01,000,000
cached @ $0.1500/M
Per request
$0.007500
in $0.004500 · out $0.003000
Per day
$37.50
5,000 requests
Per month
$1,141
152,188 requests

Estimate uses $1.50/M input · $7.50/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified Oct 22, 2026.

Input $1.50/M
Output $7.50/M
Blended (3:1 in:out) $3.00/M
Cross-model comparable price
Cached input $0.150/M

Context & limits

Context window
262,144 tokens
Max input
262,144 tokens
Max output
262,144 tokens
Modalities
vision, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input ✓ supported
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output ✓ supported
  • Prompt caching — not advertised
  • Reasoning ✓ supported

Strengths & caveats — when to pick Magistral Medium latest

Data-driven from Magistral Medium latest's percentile within chat peers.

Where it's strong

  • +long-form generation — 262,144-token max output, top-5% of peers

Watch out for

  • No major caveats flagged from public spec.

Benchmark scores

Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.

Arena ELO (coding)code· style control↑3% vs peers
Captured Oct 20, 2026
Chatbot Arena ELOgeneral· style control↓0% vs peers
Captured Oct 20, 2026
Try it

Call Magistral Medium latest via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# Magistral Medium latest via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="mistral/magistral-medium-latest",
    messages=[{"role": "user", "content": "Hello, Magistral Medium latest!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="mistral/magistral-medium-latest",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗
Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
  - model: magistral-medium-latest
    provider: mistral
    weight: 80
fallbacks:
  - model: gemini-2-0-flash
    provider: google
  - model: deepseek-v3
    provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Explore similar models

Grouped by Chatbot Arena tier (Magistral Medium latest sits at 1305 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Magistral Medium latest cost?

Input is priced at $1.50 per 1M tokens and output at $7.50 per 1M tokens (Mistral AI, last verified Oct 22, 2026).

What is the context window of Magistral Medium latest?

Magistral Medium latest supports a 262,144-token context window with up to 262,144 output tokens.

Does Magistral Medium latest support function calling?

Yes — Magistral Medium latest supports function (tool) calling.

Is Magistral Medium latest good for production?

Magistral Medium latest is well-suited for long-form generation — 262,144-token max output, top-5% of peers.

How can I route to Magistral Medium latest with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for Magistral Medium latest

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.