MAI Code 1.1 Flash

Azure AI Foundry chat Deprecates in 35d (Dec 9, 2026)
Heads-up: Azure AI Foundry has scheduled MAI Code 1.1 Flash for deprecation on Dec 9, 2026. Plan a migration. Use Agent Command Center's model fallback routing to swap models without code changes.

MAI Code 1.1 Flash is an Azure AI Foundry chat model.It supports a 256,000-token context windowwith up to 64,000 output tokens.Input is priced at $0.200/M tokens and output at $1.20/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route MAI Code 1.1 Flash 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 MAI Code 1.1 Flash spend

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

~3K in / ~400 out · 5K req/day
3,000
0256,000
400
064,000
5,000
01,000,000
cached @ $0.0200/M
Per request
$0.001080
in $0.000600 · out $0.000480
Per day
$5.40
5,000 requests
Per month
$164
152,188 requests

Estimate uses $0.2000/M input · $1.20/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 $0.200/M
Output $1.20/M
Blended (3:1 in:out) $0.450/M
Cross-model comparable price
Cached input $0.0200/M

Context & limits

Context window
256,000 tokens
Max input
256,000 tokens
Max output
64,000 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 — not advertised
  • Prompt caching ✓ supported
  • Reasoning ✓ supported

Strengths & caveats — when to pick MAI Code 1.1 Flash

Data-driven from MAI Code 1.1 Flash's percentile within chat peers.

Where it's strong

  • +multi-step reasoning and analysis tasks
  • +agentic workflows that depend on reliable tool calls
  • +document, chart, and screenshot understanding
  • +repeated long-context prompts (caching saves up to 90% on input cost)

Watch out for

  • !strict structured output — no JSON-schema enforcement, expect retry loops
  • !scheduled deprecation on Dec 9, 2026 (35 days)

Benchmarks pending

We haven't logged public benchmark scores for MAI Code 1.1 Flash yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call MAI Code 1.1 Flash 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.
# MAI Code 1.1 Flash 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="azure-ai-foundry/mai-code-1-1-flash",
    messages=[{"role": "user", "content": "Hello, MAI Code 1.1 Flash!"}],
)

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="azure-ai-foundry/mai-code-1-1-flash",
    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 ↗

Same model on other providers

mai-code-1-1-flash is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
GitHub Copilot$0.200/M$1.20/MOct 22, 2026

Explore similar models

MAI Code 1.1 Flash doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does MAI Code 1.1 Flash cost?

Input is priced at $0.200 per 1M tokens and output at $1.20 per 1M tokens (Azure AI Foundry, last verified Oct 22, 2026).

What is the context window of MAI Code 1.1 Flash?

MAI Code 1.1 Flash supports a 256,000-token context window with up to 64,000 output tokens.

Does MAI Code 1.1 Flash support function calling?

Yes — MAI Code 1.1 Flash supports function (tool) calling.

Is MAI Code 1.1 Flash good for production?

MAI Code 1.1 Flash is well-suited for multi-step reasoning and analysis tasks and agentic workflows that depend on reliable tool calls. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.

How can I route to MAI Code 1.1 Flash 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 MAI Code 1.1 Flash

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