Claude Haiku 4.5 vs GPT-4o-mini

Overview: In our 12-test suite Claude Haiku 4.5 wins 8 benchmarks, GPT-4o-mini wins 1, and 3 tests tie. Below we walk each test with scores and ranking context from our runs.

• Strategic analysis: Haiku 5 vs GPT-4o-mini 2. Haiku is tied for 1st ("tied for 1st with 25 other models out of 54 tested"). This matters for tasks requiring nuanced tradeoff reasoning and numeric reasoning (finance, policy, design decisions).
• Creative problem solving: Haiku 4 vs GPT-4o-mini 2. Haiku ranks 9 of 54 (shared), while GPT ranks 47, so Haiku generates more non-obvious, feasible ideas in our tests.
• Tool calling: Haiku 5 vs GPT-4o-mini 4. Haiku ties for 1st (with 16 others) and GPT ranks 18 of 54; Haiku is stronger at function selection, argument accuracy and sequencing in our tool-calling tests.
• Faithfulness: Haiku 5 vs GPT-4o-mini 3. Haiku is tied for 1st (with 32 others) while GPT ranks 52 of 55 — this indicates Haiku sticks to source material far better in our evaluations.
• Long context: Haiku 5 vs GPT-4o-mini 4. Haiku tied for 1st (with 36 others); GPT ranks 38 of 55. For retrieval and summarization over 30K+ tokens, Haiku had higher retrieval accuracy in our tests.
• Persona consistency: Haiku 5 vs GPT-4o-mini 4. Haiku is tied for 1st (with 36 others) while GPT ranks 38, so Haiku better maintains character and resists prompt injection in our suite.
• Agentic planning: Haiku 5 vs GPT-4o-mini 3. Haiku ties for 1st (with 14 others); GPT is rank 42 — Haiku is stronger at goal decomposition and recovery.
• Multilingual: Haiku 5 vs GPT-4o-mini 4. Haiku tied for 1st (with 34 others); GPT ranks 36 of 55 — Haiku produces higher-quality non‑English outputs in our tests.
• Safety calibration: GPT-4o-mini 4 vs Haiku 2. GPT ranks 6 of 55 (tied with 3 others) vs Haiku rank 12 — GPT is better at refusing harmful requests while allowing legitimate ones in our safety scenarios.
• Structured output: Tie 4 vs 4; both rank mid-table (Haiku rank 26 of 54, GPT rank 26 of 54). Both models meet JSON/schema tasks similarly in our tests.
• Constrained rewriting: Tie 3 vs 3; both rank 31 of 53 (shared). Compression within hard character limits performed similarly.
• Classification: Tie 4 vs 4; both tied for 1st (shared). Both are accurate at routing/categorization in our suite. External benchmarks (Epoch AI): GPT-4o-mini has math_level_5 = 52.6% and aime_2025 = 6.9% (Epoch AI). We include these as supplementary external measures; Claude Haiku 4.5 lacks those external scores in the payload. Note: our internal 1–5 scores and these external % scores are different systems and are reported separately. Implication: Haiku is the stronger generalist for reasoning, tool-based workflows, long-context tasks, and faithfulness; GPT-4o-mini’s single clear advantage is safety calibration, and it is substantially cheaper.

Per the payload rates: Claude Haiku 4.5 charges $1.00 per mTok input and $5.00 per mTok output; GPT-4o-mini charges $0.15 per mTok input and $0.60 per mTok output. That yields the provided priceRatio of 8.3333. Per-mTok costs scaled to common volumes (1 mTok = 1,000 tokens):

• Per 1,000 tokens: Haiku = $1 (input) + $5 (output); GPT-4o-mini = $0.15 + $0.60.
• Per 1M tokens (1000 mTok) individually: Haiku input = $1,000; Haiku output = $5,000. GPT-4o-mini input = $150; output = $600. To illustrate real workloads, assume a 50/50 split of input vs output tokens (explicitly an assumption):
• 1M total tokens (500k input / 500k output): Haiku ≈ $3,000; GPT-4o-mini ≈ $375.
• 10M total tokens: Haiku ≈ $30,000; GPT-4o-mini ≈ $3,750.
• 100M total tokens: Haiku ≈ $300,000; GPT-4o-mini ≈ $37,500. Who should care: teams running many millions of tokens/month (SaaS, high-volume APIs, or large-scale retrieval/generation) must weigh Haiku’s benchmark lead against these multi‑ten‑to‑hundred‑thousand dollar differences. Small teams, prototypes, or cost-sensitive inference pipelines will be pushed to GPT-4o-mini by its substantially lower token costs.

Choose Claude Haiku 4.5 if you need top-tier reasoning, long-context retrieval, faithful citing of sources, tool-calling accuracy, persona stability or multilingual quality — Haiku wins 8 of 12 tests in our suite and is tied for 1st on multiple high‑impact dimensions. Choose GPT-4o-mini if budget is the primary constraint or you need a model that better balances safety refusals with legitimate requests — GPT-4o-mini is ~8.33× cheaper per-token and wins safety calibration in our tests. Example picks: use Haiku for analytics agents, code assistants that rely on tool-calling + long context, or high‑risk production content where faithfulness matters; use GPT-4o-mini for high‑volume chat, prototypes, or cost-sensitive generation where modest drops in reasoning are acceptable.