Ministral 8B latest

Mistral AI chat

Ministral 8B 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 $0.150/M tokens and output at $0.150/M tokens. Capabilities include function calling, vision. Route Ministral 8B 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 Ministral 8B 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 @ $0.0150/M
Per request
$0.000510
in $0.000450 · out $0.000060
Per day
$2.55
5,000 requests
Per month
$77.62
152,188 requests

Estimate uses $0.1500/M input · $0.1500/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 $0.150/M
Output $0.150/M
Blended (3:1 in:out) $0.150/M
Cross-model comparable price
Cached input $0.0150/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 — not advertised

Strengths & caveats — when to pick Ministral 8B latest

Data-driven from Ministral 8B 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

  • !high cost — input + output rates are in the top 91% of priced chat peers; consider a cheaper sibling for high-volume workloads

Benchmark scores

Reported public benchmark numbers. Each row links to the source.

Captured Oct 20, 2026
Captured Oct 20, 2026
Try it

Call Ministral 8B 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.
# Ministral 8B 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/ministral-8b-latest",
    messages=[{"role": "user", "content": "Hello, Ministral 8B 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/ministral-8b-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: ministral-8b-latest
    provider: mistral
    weight: 80
fallbacks:
  - model: gpt-4
    provider: azure-openai
  - model: llama-3-3-70b-instruct
    provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Explore similar models

Grouped by Chatbot Arena tier (Ministral 8B latest sits at 1238 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Ministral 8B latest cost?

Input is priced at $0.150 per 1M tokens and output at $0.150 per 1M tokens (Mistral AI, last verified Oct 22, 2026).

What is the context window of Ministral 8B latest?

Ministral 8B latest supports a 262,144-token context window with up to 262,144 output tokens.

Does Ministral 8B latest support function calling?

Yes — Ministral 8B latest supports function (tool) calling.

Is Ministral 8B latest good for production?

Ministral 8B latest is well-suited for long-form generation — 262,144-token max output, top-5% of peers. Consider alternatives if you need high cost — input + output rates are in the top 91% of priced chat peers; consider a cheaper sibling for high-volume workloads.

How can I route to Ministral 8B 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 Ministral 8B latest

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