OpenAI

GPT-5.5

Tool callingStructured outputReasoningImage inputFile input

Default frontier GPT for coding, computer use, research, and knowledge work

Context
1.1M
Released
5mo ago
Input / 1M tokens
$5.00
Output / 1M tokens
$30.00
Cached input / 1M tokens
$0.50

Sources:models.devOpenRouter

Benchmarks

DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.

DeepSWE 1.1

Primary coding-agent benchmark · 113 tasks · Data generated 2026-09-22

Official leaderboard
67.0%
pass@1 · highest published configuration
mini-swe-agent · xhigh reasoning
pass@4
88.5%
Average cost / attempt
$7.23
Benchmark runs
4

All published configurations

Harness / reasoningpass@1pass@4Cost / attempt
mini-swe-agent · xhigh67.0%88.5%$7.23
mini-swe-agent · high64.4%90.3%$5.10
mini-swe-agent · medium54.0%77.9%$2.75
mini-swe-agent · low27.0%47.8%$1.20

pass@1 is the success rate across scored attempts; pass@4 is the share of tasks solved in at least one of four attempts. Costs are reported by DeepSWE for each configuration. These results are not directly comparable to evaluations using different harnesses. Official source JSON.

Other published benchmarks

EvaluationReported score and source
ARC-AGI-2
83.3%
Third-party evaluator · gpt-5.5_high
Reasoning effort: high
External evaluation via Epoch AI
Original-source terms apply
ARC-AGI-2
33.3%
Third-party evaluator · gpt-5.5_low
Reasoning effort: low
External evaluation via Epoch AI
Original-source terms apply
ARC-AGI-2
70.4%
Third-party evaluator · gpt-5.5_medium
Reasoning effort: medium
External evaluation via Epoch AI
Original-source terms apply
ARC-AGI-2
85.0%
Third-party evaluator · gpt-5.5_xhigh
Reasoning effort: xhigh
External evaluation via Epoch AI
Original-source terms apply
FrontierMath-Tier-4-v2-Private
72.5%
Epoch AI · gpt-5.5_xhigh
Reasoning effort: xhigh
Epoch AI evaluation
FrontierMath-Tiers-1-3-v2-Private
85.3%
Epoch AI · gpt-5.5_xhigh
Reasoning effort: xhigh
Epoch AI evaluation
GPQA diamond
90.7%
Epoch AI · gpt-5.5_low
Reasoning effort: low
Epoch AI evaluation
GPQA diamond
77.3%
Epoch AI · gpt-5.5_none
Reasoning effort: none
Epoch AI evaluation
OSWorld 2.0
13.0%
https://osworld-v2.xlang.ai/ · gpt-5.5_xhigh
Reasoning effort: xhigh
https://osworld-v2.xlang.ai/
Original-source terms apply
OTIS Mock AIME 2024-2025
84.4%
Epoch AI · gpt-5.5_low
Reasoning effort: low
Epoch AI evaluation
OTIS Mock AIME 2024-2025
57.8%
Epoch AI · gpt-5.5_none
Reasoning effort: none
Epoch AI evaluation
SimpleQA Verified
63.0%
Epoch AI · gpt-5.5_xhigh
Reasoning effort: xhigh
Epoch AI evaluation
Terminal Bench
83.1%
https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gpt-5.5_unknown
Agent: Capy · Reasoning effort: unknown
https://www.tbench.ai/leaderboard/terminal-bench/2.0
Original-source terms apply
Terminal Bench
82.2%
https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gpt-5.5_unknown
Agent: Codex CLI · Reasoning effort: unknown
https://www.tbench.ai/leaderboard/terminal-bench/2.0
Original-source terms apply
Terminal Bench
82.0%
https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gpt-5.5_unknown
Agent: Codex · Reasoning effort: unknown
https://www.tbench.ai/leaderboard/terminal-bench/2.0
Original-source terms apply
Terminal Bench
84.7%
https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gpt-5.5_unknown
Agent: NexAU-AHE · Reasoning effort: unknown
https://www.tbench.ai/leaderboard/terminal-bench/2.0
Original-source terms apply
Terminal Bench
66.1%
https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gpt-5.5_unknown
Agent: clnkr · Reasoning effort: unknown
https://www.tbench.ai/leaderboard/terminal-bench/2.0
Original-source terms apply

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Specifications

Developer
OpenAI
Model family
GPT
Type
Language model
Predecessor
—
Successor
—
Released
April 23, 2026
Model ID
openai/gpt-5.5
Openness
Closed
License
—
Input modalities
file, image, text
Output modalities
text
Modality
text+image+file->text
Tokenizer
GPT
Max output tokens
128K
Knowledge cutoff
2025-12-01
Hugging Face
—
Source freshness
Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
Source model
openai/gpt-5.5
Source family
gpt
Last updated
2026-04-23
Knowledge cutoff
2025-12-01
Model context
1.1M
Maximum input
922K
Model output limit
128K
Open weights
No
File attachments
Yes
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature control
No

Published benchmarks

BenchmarkScoreEvaluation detailsEvidence
SWE-Bench Pro58.6 · resolve rate2026-05-28Source
Terminal-Bench78.2 · success rateTerminus-2 · 2.1 · 2026-05-28Source
SWE-Atlas Codebase QnA45.43 · scoreCodexSource
SWE-Atlas Refactoring44.79 · scoreCodexSource
SWE-Atlas Test Writing42.59 · scoreCodexSource
Artificial Analysis Coding Agent Index65.3 · average pass@1Codex · xhighSource
SWE-Atlas Codebase QnA80.8 · pass@1Codex · xhighSource
SWE-Bench Pro30.9 · pass@1Codex · hard-aa · xhighSource
Terminal-Bench84.1 · pass@1Codex · xhigh · 2.1Source
Artificial Analysis Coding Agent Index60.4 · average pass@1Codex · mediumSource
SWE-Atlas Codebase QnA79.1 · pass@1Codex · mediumSource
SWE-Bench Pro26.2 · pass@1Codex · hard-aa · mediumSource
Terminal-Bench75.8 · pass@1Codex · medium · 2.1Source
Artificial Analysis Coding Agent Index57.8 · average pass@1Cursor CLI · mediumSource
SWE-Atlas Codebase QnA75 · pass@1Cursor CLI · mediumSource
SWE-Bench Pro24.9 · pass@1Cursor CLI · hard-aa · mediumSource
Terminal-Bench73.4 · pass@1Cursor CLI · medium · 2.1Source
Terminal-Bench82.7 · success rate2.0 · 2026-04-23Source
GPQA Diamond93.6 · accuracy2026-04-23Source
Humanity's Last Exam41.4 · accuracyno tools · 2026-04-23Source
Humanity's Last Exam52.2 · accuracywith tools · 2026-04-23Source
OSWorld-Verified78.7 · success rate2026-04-23Source
BrowseComp84.4 · accuracy2026-04-23Source
MMMU Pro81.2 · accuracyno tools · 2026-04-23Source
ARC-AGI-285 · accuracyVerified · 2026-04-23Source
FrontierMath51.7 · accuracyTier 1-3 · 2026-04-23Source
FrontierMath35.4 · accuracyTier 4 · 2026-04-23Source
GDPval84.9 · wins or ties2026-04-23Source
MCP Atlas75.3 · success rate2026-04-23Source
Toolathlon55.6 · success rate2026-04-23Source
τ²-Bench Telecom98 · success rateoriginal prompts · 2026-04-23Source
Complete source record (JSON)
{
  "id": "openai/gpt-5.5",
  "name": "GPT-5.5",
  "description": "Default frontier GPT for coding, computer use, research, and knowledge work",
  "family": "gpt",
  "last_updated": "2026-04-23",
  "knowledge": "2025-12-01",
  "attachment": true,
  "reasoning": true,
  "tool_call": true,
  "structured_output": true,
  "temperature": false,
  "modalities": {
    "input": [
      "text",
      "image",
      "pdf"
    ],
    "output": [
      "text"
    ]
  },
  "limit": {
    "context": 1050000,
    "input": 922000,
    "output": 128000
  },
  "benchmarks": [
    {
      "name": "SWE-Bench Pro",
      "score": 58.6,
      "source": "https://www.anthropic.com/news/claude-opus-4-8",
      "metric": "resolve rate",
      "date": "2026-05-28"
    },
    {
      "name": "Terminal-Bench",
      "score": 78.2,
      "source": "https://www.anthropic.com/news/claude-opus-4-8",
      "metric": "success rate",
      "harness": "Terminus-2",
      "version": "2.1",
      "date": "2026-05-28"
    },
    {
      "name": "SWE-Atlas Codebase QnA",
      "score": 45.43,
      "source": "https://labs.scale.com/leaderboard/sweatlas-qna",
      "metric": "score",
      "harness": "Codex"
    },
    {
      "name": "SWE-Atlas Refactoring",
      "score": 44.79,
      "source": "https://labs.scale.com/leaderboard/sweatlas-refactoring",
      "metric": "score",
      "harness": "Codex"
    },
    {
      "name": "SWE-Atlas Test Writing",
      "score": 42.59,
      "source": "https://labs.scale.com/leaderboard/sweatlas-tw",
      "metric": "score",
      "harness": "Codex"
    },
    {
      "name": "Artificial Analysis Coding Agent Index",
      "score": 65.3,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "average pass@1",
      "harness": "Codex",
      "variant": "xhigh"
    },
    {
      "name": "SWE-Atlas Codebase QnA",
      "score": 80.8,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "xhigh"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 30.9,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "xhigh",
      "dataset": "hard-aa"
    },
    {
      "name": "Terminal-Bench",
      "score": 84.1,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "xhigh",
      "version": "2.1"
    },
    {
      "name": "Artificial Analysis Coding Agent Index",
      "score": 60.4,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "average pass@1",
      "harness": "Codex",
      "variant": "medium"
    },
    {
      "name": "SWE-Atlas Codebase QnA",
      "score": 79.1,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "medium"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 26.2,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "medium",
      "dataset": "hard-aa"
    },
    {
      "name": "Terminal-Bench",
      "score": 75.8,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Codex",
      "variant": "medium",
      "version": "2.1"
    },
    {
      "name": "Artificial Analysis Coding Agent Index",
      "score": 57.8,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "average pass@1",
      "harness": "Cursor CLI",
      "variant": "medium"
    },
    {
      "name": "SWE-Atlas Codebase QnA",
      "score": 75,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Cursor CLI",
      "variant": "medium"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 24.9,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Cursor CLI",
      "variant": "medium",
      "dataset": "hard-aa"
    },
    {
      "name": "Terminal-Bench",
      "score": 73.4,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Cursor CLI",
      "variant": "medium",
      "version": "2.1"
    },
    {
      "name": "Terminal-Bench",
      "score": 82.7,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "success rate",
      "version": "2.0",
      "date": "2026-04-23"
    },
    {
      "name": "GPQA Diamond",
      "score": 93.6,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "date": "2026-04-23"
    },
    {
      "name": "Humanity's Last Exam",
      "score": 41.4,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "variant": "no tools",
      "date": "2026-04-23"
    },
    {
      "name": "Humanity's Last Exam",
      "score": 52.2,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "variant": "with tools",
      "date": "2026-04-23"
    },
    {
      "name": "OSWorld-Verified",
      "score": 78.7,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "success rate",
      "date": "2026-04-23"
    },
    {
      "name": "BrowseComp",
      "score": 84.4,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "date": "2026-04-23"
    },
    {
      "name": "MMMU Pro",
      "score": 81.2,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "variant": "no tools",
      "date": "2026-04-23"
    },
    {
      "name": "ARC-AGI-2",
      "score": 85,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "variant": "Verified",
      "date": "2026-04-23"
    },
    {
      "name": "FrontierMath",
      "score": 51.7,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "dataset": "Tier 1-3",
      "date": "2026-04-23"
    },
    {
      "name": "FrontierMath",
      "score": 35.4,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "accuracy",
      "dataset": "Tier 4",
      "date": "2026-04-23"
    },
    {
      "name": "GDPval",
      "score": 84.9,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "wins or ties",
      "date": "2026-04-23"
    },
    {
      "name": "MCP Atlas",
      "score": 75.3,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "success rate",
      "date": "2026-04-23"
    },
    {
      "name": "Toolathlon",
      "score": 55.6,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "success rate",
      "date": "2026-04-23"
    },
    {
      "name": "τ²-Bench Telecom",
      "score": 98,
      "source": "https://openai.com/index/introducing-gpt-5-5/",
      "metric": "success rate",
      "variant": "original prompts",
      "date": "2026-04-23"
    }
  ],
  "release_date": "2026-04-23",
  "open_weights": false
}

Infrastructure

Provider availability

All providers
ProviderEndpointContextInput /M tokensOutput /M tokensCached input /M tokensCache write /M tokensUptime 1dData handling
OpenAIopenai/flex1.1M$2.50$15.00$0.25——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

OpenAIopenai/flexBatch pricing1.1M$2.50$15.00$0.25——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure1.1M$5.00$30.00$0.50—99.93%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

AzureazureBatch pricing1.1M$5.00$30.00$0.50—100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

OpenAIopenai1.1M$5.00$30.00$0.50—100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

OpenAIopenaiBatch pricing1.1M$5.00$30.00$0.50—100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Amazon Bedrockamazon-bedrock/us-east-11.1M$5.50$33.00$0.55——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Amazon Bedrockamazon-bedrock/us-east-1Batch pricing1.1M$5.50$33.00$0.55——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure/us1.1M$5.50$33.00$0.55—100.00%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure/eu1.1M$5.50$33.00$0.55——
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure/usBatch pricing1.1M$5.50$33.00$0.55—100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure/euBatch pricing1.1M$5.50$33.00$0.55——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

OpenAIopenai/fast1.1M$12.50$75.00$1.25——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

OpenAIopenai/fastBatch pricing1.1M$12.50$75.00$1.25——
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Provider data:OpenRouter

Text provenance

EU · product-scoped

OpenAI textGrain watermarking

In the EU, ChatGPT-generated text uses textGrain. OpenAI says API customers can opt in globally for select models, so watermarking depends on the product surface and configuration.

Official explanation