Claude Haiku 4.5
Azure AI Foundry chat Deprecates in 11d (Nov 15, 2026)model fallback routing to swap models without code changes.
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.
Estimate Claude Haiku 4.5 spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
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 Oct 22, 2026.
| Input | $1.00/M | |
| Output | $5.00/M | |
| Blended (3:1 in:out) | $2.00/M Cross-model comparable price | |
| Cached input | $0.1000/M |
Context & 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
Strengths & caveats — when to pick Claude Haiku 4.5
Data-driven from Claude Haiku 4.5's percentile within chat peers.
Where it's strong
- +PDF input — only 18% of chat models on Future AGI advertise this
Watch out for
- !scheduled deprecation on Nov 15, 2026 (11 days)
Benchmark scores
Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.
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.
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"))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: gpt-5-2-chat-latest
provider: openai
- model: glm-5-3-flash
provider: zai
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true } Same model on other providers
claude-haiku-4-5 is also available via 4 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| Google Vertex AI | $1.00/M | $5.00/M | Oct 22, 2026 |
| Anthropic | $1.00/M | $5.00/M | Oct 22, 2026 |
| GitHub Copilot | $1.00/M | $5.00/M | Oct 22, 2026 |
| Snowflake Cortex | $1.00/M | $5.00/M | Oct 22, 2026 |
Explore similar models
Grouped by Chatbot Arena tier (Claude Haiku 4.5 sits at 1415 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.
- GPT-5.4Azure AI Foundry · $2.50/M in · $15.00/M out · 922,000 ctxCompare side-by-side →
- DeepSeek R1Azure AI Foundry · $1.35/M in · $5.40/M outCompare side-by-side →
- GPT-5.5 (2026-04-23)Azure AI Foundry · $5.00/M in · $30.00/M out · 922,000 ctxCompare side-by-side →
- Claude Opus 4.7Azure AI Foundry · $5.00/M in · $25.00/M out · 1,000,000 ctxView model →
- GPT-5.4OpenAI · $2.50/M in · $15.00/M out · 1,050,000 ctxCompare side-by-side →
- GPT-5.4 (2026-03-05)OpenAI · $2.50/M in · $15.00/M out · 1,050,000 ctxCompare side-by-side →
- Grok 4.1 FastxAI · $0.200/M in · $0.500/M out · 2,000,000 ctxCompare side-by-side →
- DeepSeek R1Snowflake Cortex · $1.35/M in · $5.40/M out · 128,000 ctxCompare side-by-side →
≥30 ELO higher
- Gemini 4 ArgonGoogle AI · $2.00/M in · $10.00/M out · 1,048,576 ctxCompare side-by-side →
- GPT-5.5 (2026-04-23)OpenAI · $5.00/M in · $30.00/M out · 1,050,000 ctxCompare side-by-side →
- GPT-5.5OpenAI · $5.00/M in · $30.00/M out · 1,050,000 ctxCompare side-by-side →
- GLM 5.2Alibaba DashScope · $1.40/M in · $4.40/M out · 1,048,576 ctxCompare side-by-side →
25–100 ELO lower, ≤50% of price
- GPT-5 nanoAzure OpenAI · $0.0500/M in · $0.400/M out · 272,000 ctxView model →
- GPT-5 nano (2025-08-07)Azure OpenAI · $0.0500/M in · $0.400/M out · 272,000 ctxView model →
- GPT-4.1 nano (2025-04-14)Azure OpenAI · $0.1000/M in · $0.400/M out · 1,047,576 ctxView model →
- GPT-4o miniAzure OpenAI · $0.150/M in · $0.600/M out · 128,000 ctxView model →
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 Oct 22, 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 18% of chat models on Future AGI advertise this. Consider alternatives if you need scheduled deprecation on Nov 15, 2026 (11 days).
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.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.