Models & Pricing

GPT-5.5 Pro vs Claude Opus 5.5

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ComparisonGPT-5.5 Pro
gpt-5.5-pro
Claude Opus 5.5
claude-opus-5-5
TypeChatChat
Best forComplex reasoning, multi-step analysis and difficult codingComplex reasoning, multi-step analysis and difficult coding
TokenRex price$30.00 in / $180.00 out per 1M tokens$4.00 in / $20.00 out per 1M tokens
Cached input / 1M tokens$3.00 per 1M tokens$0.20 per 1M tokens
Cache write / 1M tokensNo extra fee$5.00 per 1M tokens
Cached outputNot offered · standard output rate appliesNot offered · standard output rate applies
Web search$10.00 per 1K searches$10.00 per 1K searches
Market price$30.00 in / $180.00 out per 1M tokens$4.00 in / $20.00 out per 1M tokens
Context window (provider)1,050,000 tokens1,000,000 tokens
Input token limit (provider)Within the context windowWithin the context window
Maximum output128,000 tokens128,000 tokens
Knowledge cutoffDec 01, 2025Jun 2026
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 evidence9 source-linked results17 source-linked results
ARC-AGI-1
96.5%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. ARC-AGI-1 96.5% 92nd percentile · rank 9 of 97 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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ARC-AGI-2
84.6%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. ARC-AGI-2 84.6% 91st percentile · rank 10 of 99 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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BrowseComp
90.1%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. BrowseComp 90.1% 88th percentile · rank 8 of 60 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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Humanity's Last Exam (with tools)
57.2%

Published configuration: {"variant": "Pro", "tools": true, "third_party_aggregator": true}. Humanity's Last Exam 57.2% with tools / 43.1% no tools Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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Humanity's Last Exam (no tools)
43.1%

Published configuration: {"variant": "Pro", "tools": false, "third_party_aggregator": true}. Humanity's Last Exam 57.2% with tools / 43.1% no tools Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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FrontierMath
52.4%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. FrontierMath 2025-02-28 Private 52.4% 83rd percentile · rank 7 of 37 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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FrontierMath Tier 4
39.6%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. FrontierMath Tier 4 2025-07-01 Private 39.6% 78th percentile · rank 6 of 24 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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GDPval
82.3%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. GDPval 82.3% Generalization · 88th percentile · rank 3 of 18 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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SimpleBench
76.9%

Published configuration: {"variant": "Pro", "third_party_aggregator": true}. SimpleBench 76.9% 94th percentile · rank 3 of 36 Published model-family result, not a test of TokenRex or its default effort.

BenchmarkList - GPT-5.5 Pro
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FrontierCode v1.1 (Main)—
54.4%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
54.64%

Cognition FrontierCode 1.1; Claude Opus 5.5; medium effort; claude-code harness; Main subset (100 tasks). Published weighted rubric score (new_score × 100), not the all-or-nothing pass rate; solution-source violations score zero. Source field new_score=0.5464. Publisher evaluation, not a TokenRex measurement; provider effort configuration is not a guarantee of the API's fixed thinking budget.

Cognition · FrontierCode 1.1 original leaderboard
CursorBench 4.0—
57.8%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
56%

Row explicitly labeled 'Opus 5.5 Extra High' (xhigh) at 56.0%, $6.98/task. Kept distinct from the existing 57.8% entry, which is Anthropic's own self-reported max-effort figure from the launch page, and from CursorBench's own 'Opus 5.5 Max' row (57.8%, $13.43/task) — same number as Anthropic's but a separately sourced/priced data point.

Cursor · CursorBench 4.0 public leaderboard
AutomationBench—
40%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
Humanity’s Last Exam (with tools)—
67.7%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
Terminal-Bench-Science 0.1—
58.7%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
62%

Explicitly the xhigh effort configuration ('Claude Opus 5.5 (xhigh)'); AA also separately reports 59% at max effort for the same model on this benchmark — kept distinct and not merged. Independent AA harness, not Anthropic's own 58.7% (max effort) figure already on file.

Artificial Analysis · Terminal-Bench-Science 0.1 leaderboard launch post (LinkedIn)
OSWorld 2.1 (partial)—
81.8%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
Chartography (with tools)—
89%

Provider launch evaluation with adaptive thinking at max effort and production safeguards; not the default medium catalog configuration.

Anthropic · Claude Opus 5.5 launch evaluation
Terminal-Bench 4.0—
66.4%

Launch report explicitly states xhigh effort, standard error ±2.6 points; production safeguards. Not a medium or fast-mode measurement.

Anthropic · Claude Opus 5.5 launch evaluation
60%

Explicitly the Xhigh effort configuration ('Claude Opus 5.5 (Xhigh, Default Fallback)') on AA's independently-run Terminal-Bench 4.0 harness — matches the requested Opus 5.5 xhigh condition exactly, not max/fast/default. Distinct from Anthropic's own self-reported xhigh figure of 66.4% already on file (different methodology/harness) and from AA's narrative max-effort figure of 59.6% quoted in AA's launch article.

Artificial Analysis · Opus 5.5 (Xhigh) vs Opus 5 (High) comparison
Artificial Analysis Intelligence Index—
58index

Independent AA run, 'Claude Opus 5.5 (Max, Default Fallback)' configuration — AA's max-effort-with-fallback harness, not the catalog medium default. Not comparable to the Xhigh config (56) or High config (54) also reported by AA.

Artificial Analysis · Claude Opus 5.5 release page
Humanity's Last Exam—
61.4%

Independent AA evaluation, reported for the top-scoring (max-effort/fallback) AA configuration used for the Intelligence Index; AA states this is the new best score on this eval, ahead of Fable 5.1's prior 59.1%. Effort level for this specific sub-score is implied (Intelligence Index default config), not separately confirmed for every effort tier.

Artificial Analysis · 'Claude Opus 5.5 takes the top spot' article
SciCode—
66.9%

Independent AA evaluation under the Intelligence Index max-effort/fallback configuration; AA reports this surpasses Fable 5.1's prior best of 63.1%.

Artificial Analysis · 'Claude Opus 5.5 takes the top spot' article
AA-Briefcase v1.1 (Elo)—
1822Elo

AA's private frontier knowledge-work evaluation using the open-source Stirrup reference agent harness; max-effort/fallback configuration (the configuration AA headlines for Opus 5.5). Not the Xhigh-specific Briefcase score (1768) also published by AA.

Artificial Analysis · 'Claude Opus 5.5 takes the top spot' article
FrontierCode v1.1 (Extended)—
65.27%

Cognition FrontierCode 1.1; Claude Opus 5.5; medium effort; claude-code harness; Extended subset (150 tasks). Published weighted rubric score (new_score × 100), not the all-or-nothing pass rate; solution-source violations score zero. Source field new_score=0.6527. Publisher evaluation, not a TokenRex measurement; provider effort configuration is not a guarantee of the API's fixed thinking budget.

Cognition · FrontierCode 1.1 original leaderboard

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-5.5 Pro

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 Opus 5.5

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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