Model
Claude Haiku 4.5 NO.06
Fastest, cheapest Claude — snappy everyday tasks at scale.
Anthropic · Claude · Fast · Closed weights
Specification
11 fields
Fig.01 — Claude — Anthropic
USA
- Context window
- 200Ktokens
- Max output
- 64Ktokens
- Input price
- $1/ 1M
- Output price
- $5/ 1M
- Cached input
- $0.10/ 1M
- Throughput
- —
- Class
- Fast
- Modalities
- Text, Image, Pdf
- Weights
- Closed
- Knowledge cutoff
- Jul 2025
- Released
- Oct 2025
Overview
Claude Haiku 4.5 is Anthropic's fastest and cheapest model, built for high-volume, latency-sensitive work. It delivers surprisingly strong reasoning and coding for its price and is a great router target for the bulk of simpler traffic. Escalate to Sonnet or Opus when a task needs deeper reasoning or long-horizon reliability.
Strengths
- Fastest and cheapest Claude
- Strong quality for its tier
- Great for high-volume routing
- Low latency for real-time work
- 200K context
Trade-offs
- Smaller 200K context vs 1M on higher tiers
- Not for hard long-horizon agentic work
- Lower peak reasoning than larger Claude models
Fit
Best for
- High-volume classification and extraction
- Low-latency chat and autocomplete
- Simple coding and edits
- Cheap agent sub-steps
Not ideal for
- Complex autonomous coding
- Deep multi-step reasoning tasks
- Very long-context tasks (>200K)
Capabilities
Normalized 0—100
Ten axes, normalized 0–100 and scored the same way across the whole catalog — so a 78 here means what a 78 means anywhere else on the bench.
Fig.02 — Capability radar
0 — 100
- Reasoning
- 78
- Coding
- 78
- Math
- 80
- Writing
- 82
- Knowledge
- 80
- Speed
- 93
- Agentic
- 75
- Vision
- 78
- Multilingual
- 82
- Long Context
- 80
Benchmarks
04 results
Public results, with independent third-party runs marked. Bars normalize percentages against 100 and Elo ratings against a 1500 ceiling.
Independent index
Artificial Analysis Intelligence Index
Composite of ~9–10 independent evals · Artificial Analysis
30/ 100
- Artificial Analysis Intelligence IndexIndependentGeneral · Artificial Analysis
- 30%
- SWE-bench VerifiedIndependentCoding · SWE-bench
- 73.3%
- SWE-bench ProIndependentCoding · SWE-bench Pro
- 39.5%
- AIME 2025Math · Vendor-reported
- 80.7%
Alternatives
03 comparable
Models in roughly the same class — the ones worth weighing against this record.
Index
Record 06 of 41