Models & Pricing

GPT-5.4 Mini vs Claude Haiku 4.5

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ComparisonGPT-5.4 Mini
gpt-5.4-mini
Claude Haiku 4.5
claude-haiku-4-5
TypeChatChat
Best forFast, low-cost replies and high-volume everyday tasksFast, low-cost replies and high-volume everyday tasks
TokenRex price$0.75 in / $4.50 out per 1M tokens$1.00 in / $5.00 out per 1M tokens
Cached input / 1M tokens$0.075 per 1M tokens$0.10 per 1M tokens
Cache write / 1M tokensNo extra fee$1.25 per 1M tokens
Cached outputNot offered · standard output rate appliesNot offered · standard output rate applies
Market price$0.75 in / $4.50 out per 1M tokens$1.00 in / $5.00 out per 1M tokens
Context window (provider)400,000 tokens200,000 tokens
Input token limit (provider)Within the context windowWithin the context window
Maximum output128,000 tokens64,000 tokens
Knowledge cutoffAug 31, 2025Feb 2025
Vendor input modalitiesNot verifiedText, Image
Vendor output modalitiesNot verifiedText
TokenRex endpointsPOST /v1/chat/completionsPOST /v1/chat/completions · POST /v1/messages
TokenRex inputText, Image/PDF content through the chat bridgeText, Image/PDF content through the chat bridge
TokenRex outputTextText
Benchmarks
Benchmark evidence5 source-linked results1 source-linked results
SWE-Bench Pro (Public)
54.4%

Published reasoning effort: xhigh. SWE-Bench Pro (Public) | 57.7% | 54.4% | 52.4% | 45.7% | Published model-family result, not a test of TokenRex or its default effort.

OpenAI - Introducing GPT-5.4 mini and nano
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Terminal-Bench 2.0
60%

Published reasoning effort: xhigh. Terminal-Bench 2.0 | 75.1% | 60.0% | 46.3% | 38.2% | Published model-family result, not a test of TokenRex or its default effort.

OpenAI - Introducing GPT-5.4 mini and nano
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Toolathlon
42.9%

Published reasoning effort: xhigh. Toolathlon | 54.6% | 42.9% | 35.5% | 26.9% | Published model-family result, not a test of TokenRex or its default effort.

OpenAI - Introducing GPT-5.4 mini and nano
—
GPQA Diamond
88%

Published reasoning effort: xhigh. GPQA Diamond | 93.0% | 88.0% | 82.8% | 81.6% | Published model-family result, not a test of TokenRex or its default effort.

OpenAI - Introducing GPT-5.4 mini and nano
—
OSWorld-Verified
72.1%

Published reasoning effort: xhigh. OSWorld-Verified | 75.0% | 72.1% | 39.0% | 42.0% | Published model-family result, not a test of TokenRex or its default effort.

OpenAI - Introducing GPT-5.4 mini and nano
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SWE-bench Verified—
73.3%

Anthropic methodology footnote: simple bash+file-edit scaffold, averaged over 50 trials, no test-time compute, 128K thinking budget, default sampling, full 500-problem set, with a prompt addendum instructing heavy tool use. Haiku 4.5's catalog default is Extended thinking (no explicit low/medium/high effort knob), so this is treated as the base/default-thinking configuration, not a stripped-down no-thinking run.

Anthropic · Introducing Claude Haiku 4.5

No overall score, winner or cost-versus-score frontier is calculated without comparable, attributable benchmark evidence. Different test configurations appear separately. Vendor capabilities are distinct from TokenRex API support.

— means no published value or no matching capability. Provider token limits are not tested gateway guarantees; TokenRex media controls and response formats are listed separately.

GPT-5.4 Mini

Sources and verification

Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.

Research notes (1)
  • Published provider limits; maximum-capacity requests have not been independently exercised through TokenRex. Thinking-level variants use the same provider model; reasoning and answer tokens share the output budget.

Claude Haiku 4.5

Sources and verification

Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.

Research notes (1)
  • Published provider limits; maximum-capacity requests have not been independently exercised through TokenRex. Thinking-level variants use the same provider model; reasoning and answer tokens share the output budget.

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