Claude Haiku 4.5

Azure AI Foundry chat

Claude Haiku 4.5 is an Azure AI Foundry chat model.It supports a 200,000-token context windowwith up to 64,000 output tokens.Input is priced at $1.00/M tokens and output at $5.00/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route Claude Haiku 4.5 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate Claude Haiku 4.5 spend

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

~3K in / ~400 out · 5K req/day
3,000
0200,000
400
064,000
5,000
01,000,000
cached @ $0.1000/M
Per request
$0.005000
in $0.003000 · out $0.002000
Per day
$25.00
5,000 requests
Per month
$761
152,188 requests

Estimate uses $1.00/M input · $5.00/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 May 12, 2026.

Input $1.00/M
Output $5.00/M
Cached input $0.1000/M

Limits

Context window
200,000 tokens
Max input
200,000 tokens
Max output
64,000 tokens
Modalities
vision, pdf, text

Capabilities

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

Where it's strong

  • +PDF input — only 16% of chat models on Future AGI advertise this
  • +prompt caching — only 23% of chat models on Future AGI advertise this

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.

HumanEvalcode· 0-shot↑3% vs peers
Captured May 12, 2026
BFCL v3agent· multi-turn
Captured May 12, 2026
Chatbot Arena ELOgeneral· overall
Captured May 12, 2026
MMLU-Proreasoning· 0-shot↓8% vs peers
Captured May 12, 2026
GPQA Diamondreasoning· 0-shot CoT↓22% vs peers
Captured May 12, 2026
SWE-bench Verifiedagent· agentic↑11% vs peers
Captured May 12, 2026
Try it

Call Claude Haiku 4.5 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.
# Claude Haiku 4.5 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/claude-haiku-4-5",
    messages=[{"role": "user", "content": "Hello, Claude Haiku 4.5!"}],
)

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/claude-haiku-4-5",
    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: claude-haiku-4-5
    provider: azure-ai-foundry
    weight: 80
fallbacks:
  - model: deepseek-r1
    provider: deepseek
  - model: gemini-2-5-flash
    provider: vertex-ai
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

claude-haiku-4-5 is also available via 3 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Anthropic$1.00/M$5.00/MMay 12, 2026
GitHub CopilotMay 12, 2026
Google Vertex AI$1.00/M$5.00/MMay 12, 2026

Compare with similar models

Grouped by Chatbot Arena tier (Claude Haiku 4.5 sits at 1310 ELO).

FAQ

How much does Claude Haiku 4.5 cost?

Input is priced at $1.00 per 1M tokens and output at $5.00 per 1M tokens (Azure AI Foundry, last verified May 12, 2026).

What is the context window of Claude Haiku 4.5?

Claude Haiku 4.5 supports a 200,000-token context window with up to 64,000 output tokens.

Does Claude Haiku 4.5 support function calling?

Yes — Claude Haiku 4.5 supports function (tool) calling.

Is Claude Haiku 4.5 good for production?

Claude Haiku 4.5 is well-suited for PDF input — only 16% of chat models on Future AGI advertise this and prompt caching — only 23% of chat models on Future AGI advertise this.

How can I route to Claude Haiku 4.5 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 Claude Haiku 4.5

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