AI model comparison

Claude Haiku 4.5 vs GPT-5 mini

Comparing two fast, lower-cost models for high-volume classification, routing, and lightweight extraction where latency and unit price matter most.

Quick answer: GPT-5 mini lists the lower prices ($0.25/$2 per 1M versus $1/$5) and the larger context window (400k versus 200k); Claude Haiku 4.5 is positioned as the quality-stronger small tier at a higher list price.

Pricing & context

All figures below are list prices pulled directly from the Harpd pricing registry (last verified 2026-08-18). Prices change often — open each model’s source link to confirm before budgeting. Machine-readable copy: /data/llm-pricing.json.

MetricClaude Haiku 4.5GPT-5 mini
ProviderAnthropicOpenAI
Input / 1M tokens$1$0.25
Output / 1M tokens$5$2
Cached input / 1M tokens$0.1$0.03
Batch discount50% off50% off
Context window200,000 tokens400,000 tokens
SourceAnthropic pricing ↗OpenAI pricing ↗
GPT-5 mini lists the lower cost for this workload.

$325 vs $1,000 / month (100k calls, 5k in / 1k out)

Last updated
Methodology
Computed from list prices per 1M tokens; excludes prompt caching and batch discounts.
GPT-5 mini lists the larger context window.

400,000 tokens

Last updated
Harpd has not measured these two models head-to-head yet.

First benchmark: JSON extraction, 100 real tasks — target ship 2026-09-15

Last updated
Methodology
Until then, no performance win is claimed on this page — validate both models on your own tasks.
Claude Haiku 4.5

Capabilities

Claude Haiku 4.5 is positioned as a fast, cost-efficient model with strong performance for its tier, a 200k context window, and prompt caching.

Best for

High-volume tasks where small-tier output quality matters enough to pay roughly 4× GPT-5 mini's list price.

Limitations

$1/$5 per 1M is 4–2.5× GPT-5 mini's list price, and the 200k window is half of GPT-5 mini's.

GPT-5 mini

Capabilities

GPT-5 mini is a small, low-latency model with a 400k context window, prompt caching, and a very low per-token price aimed at high-volume calls.

Best for

Pure-volume classification, routing and extraction where unit cost and a 400k window matter most.

Limitations

Small reasoning models can drop below your quality bar on nuanced extraction — only a sampled evaluation on your tasks shows whether the 80% saving survives.

Recommendation

Both are designed for cheap, high-throughput work, so the pragmatic move is to benchmark each on your highest-volume path. Claude Haiku 4.5 tends to be chosen where output quality at the small tier matters; GPT-5 mini’s lower price suits pure volume. Neither is universally “better” — test both on your real traffic before standardizing.

Updated 2026-08-18. Sources: Anthropic and OpenAI official pricing pages (verified 2026-08-18); no Harpd-measured benchmark yet.

Methodology & sources

Prices on this page come from the Harpd pricing registry, which mirrors the officialAnthropic and OpenAI pricing pages and was last verified 2026-08-18. Capability notes summarize documented provider positioning — they are not Harpd measurements. Cheaper-cost claims are computed from the registry at a fixed reference workload, so they are reproducible from the published dataset. Read the pricing methodology and themodel replacement guide before switching a production workload.

Answer

Price tells you what a model costs. It does not tell you whether it can replace your current model on your real tasks.

Read the evaluation guide
Evidence

Related comparisons

Gemini 2.5 Flash vs Claude Haiku 4.5Gemini 2.5 Flash lists lower prices ($0.30/$2.50 per 1M versus $1/$5) and a 1M-token context window versus 200k; Claude Haiku 4.5 is positioned as the dependable fast tier for quality-sensitive short tasks.GPT-5 mini vs Llama 3.1 70BGPT-5 mini lists the cheaper input ($0.25 vs $0.88 per 1M) while Llama 3.1 70B lists the cheaper output ($0.88 vs $2); the deeper difference is managed convenience versus open-weight portability.

Explore related tools

Model Compare

Side-by-side pricing and capability explorer for every model in the registry.

LLM Pricing

Full list-price table across providers, updated from official sources.

Benchmarks

Open benchmark data — methodology, datasets and published results.

Claude Haiku 4.5 vs GPT-5 mini, answered

Which is cheaper, Claude Haiku 4.5 or GPT-5 mini?
GPT-5 mini lists the lower cost at Harpd's reference workload (100,000 calls/month, 5,000 input / 1,000 output tokens): about $325 versus $1,000 per month at list prices (0.25/2 vs 1/5 USD per 1M input/output tokens). The mix matters: if your workload is output-heavy, recompute with the model compare calculator.
What is the main difference between Claude Haiku 4.5 and GPT-5 mini?
GPT-5 mini lists the lower prices ($0.25/$2 per 1M versus $1/$5) and the larger context window (400k versus 200k); Claude Haiku 4.5 is positioned as the quality-stronger small tier at a higher list price.
Which has the larger context window?
GPT-5 mini lists 400,000 tokens versus 200,000 for Claude Haiku 4.5, according to the Harpd pricing registry (last verified 2026-08-18).
Which should I choose?
Both are designed for cheap, high-throughput work, so the pragmatic move is to benchmark each on your highest-volume path. Claude Haiku 4.5 tends to be chosen where output quality at the small tier matters; GPT-5 mini’s lower price suits pure volume. Neither is universally “better” — test both on your real traffic before standardizing.