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GPT-5.6 Terra

OpenAI

Released
June 26, 2026
Data date
August 11, 2026

Category view

Position within the category

This overview uses only published data from matching cohorts. Missing values never change a rank.

The index averages rank percentiles from 4 documented comparison cohorts. Only models with complete coverage receive a position.

Position
Rank 10 of 26
Index score
59.1 / 100
Coverage
4 / 4

Leaderboard

1Claude Opus 588.9 / 100
2Gemini 3.8 Flash88.5 / 100
3Claude Fable 583.2 / 100
9Gemini 3.6 Flash63 / 100
10GPT-5.6 Terra, Current model59.1 / 100
11Gemini 3.5 Flash58.7 / 100
25MiMo-V2.5-Pro12.5 / 100

Measurements

Comparable benchmark results

Each chart contains exactly one source, one measurement series, and one stored comparison cohort. Bars show the position. The measured value appears on the right.

LiveBench

77.94 points · Rank 4 of 4

Comparison cohort: livebench-2026-06-25-max · Data date: September 2, 2026

1.Claude Fable 582.97 points
2.GPT-5.6 Sol81.05 points
3.GPT-5.580.19 points
4.GPT-5.6 Terra, Current model77.94 points

4 of 4 model versions shown in this chart. A higher value ranks first.

23 objectively scored tasks across seven categories.

Source: LiveBenchParticipants: 4

LiveBench

90.6 points · Rank 2 of 4

Task: Reasoning · Comparison cohort: livebench-2026-06-25-reasoning-max · Data date: September 2, 2026

1.GPT-5.6 Sol91.7 points
2.GPT-5.6 Terra, Current model90.6 points
3.Claude Fable 589.7 points
3.GPT-5.589.7 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Reasoning category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

78.2 points · Rank 4 of 4

Task: Coding · Comparison cohort: livebench-2026-06-25-coding-max · Data date: September 2, 2026

1.Claude Fable 586 points
2.GPT-5.6 Sol83.9 points
3.GPT-5.582.1 points
4.GPT-5.6 Terra, Current model78.2 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Coding category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

54.9 points · Rank 3 of 4

Task: Agentic coding · Comparison cohort: livebench-2026-06-25-agentic-coding-max · Data date: September 2, 2026

1.Claude Fable 562.2 points
2.GPT-5.6 Sol56.2 points
3.GPT-5.6 Terra, Current model54.9 points
4.GPT-5.554 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Agentic coding category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

94.9 points · Rank 4 of 4

Task: Mathematics · Comparison cohort: livebench-2026-06-25-mathematics-max · Data date: September 2, 2026

1.GPT-5.6 Sol96.2 points
2.Claude Fable 596 points
3.GPT-5.595.9 points
4.GPT-5.6 Terra, Current model94.9 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Mathematics category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

79.3 points · Rank 4 of 4

Task: Data analysis · Comparison cohort: livebench-2026-06-25-data-analysis-max · Data date: September 2, 2026

1.GPT-5.581.6 points
2.Claude Fable 580.5 points
3.GPT-5.6 Sol79.8 points
4.GPT-5.6 Terra, Current model79.3 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Data analysis category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

82.9 points · Rank 4 of 4

Task: Language · Comparison cohort: livebench-2026-06-25-language-max · Data date: September 2, 2026

1.Claude Fable 590.7 points
2.GPT-5.6 Sol87.7 points
3.GPT-5.587.4 points
4.GPT-5.6 Terra, Current model82.9 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Language category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

LiveBench

64.6 points · Rank 4 of 4

Task: Instruction following · Comparison cohort: livebench-2026-06-25-instruction-following-max · Data date: September 2, 2026

1.Claude Fable 575.8 points
2.GPT-5.6 Sol71.8 points
3.GPT-5.570.7 points
4.GPT-5.6 Terra, Current model64.6 points

4 of 4 model versions shown in this chart. A higher value ranks first.

Instruction following category inside the same LiveBench release.

Source: LiveBenchParticipants: 4

BrowseComp

87.5% · Rank 2 of 5

Comparison cohort: browsecomp-openai-gpt-5-6-table · Data date: September 2, 2026

1.Claude Mythos 588%
2.GPT-5.6 Terra, Current model87.5%
3.Gemini 3.1 Pro Preview85.9%
4.GPT-5.584.4%
5.GPT-5.6 Luna83.3%

5 of 5 model versions shown in this chart. A higher value ranks first.

Cross-vendor comparison table with browsing tools. Exact agent systems differ.

Editorial selection from the vendor table, not a complete extract of the comparison cohort.

Source: OpenAIParticipants: 5

SWE-Bench Pro

63.4% · Rank 4 of 5

Comparison cohort: swe-pro-openai-gpt-5-6-release · Data date: September 2, 2026

1.Claude Mythos 580.3%
2.Claude Fable 580%
3.GPT-5.6 Sol64.6%
4.GPT-5.6 Terra, Current model63.4%
5.GPT-5.6 Luna62.7%

5 of 5 model versions shown in this chart. A higher value ranks first.

Comparison table published by OpenAI. Not a Gradually test.

After an audit, OpenAI estimates that about 30% of the public tasks are broken. The result therefore remains a disputed secondary signal. The rows are an editorial selection from the respective comparison table.

Source: OpenAIParticipants: 5

Profile

Specifications and access

Published information about this model. Unknown values are not estimated.

Model type
ProprietarySource
Context window
1,050,000 tokensSource
Knowledge cutoff
February 16, 2026Source
Notes
Balanced tier of the GPT-5.6 family. Generally available from 2026-07-09. Default model for Free and Go users on ChatGPT Work and Codex, effort-selectable on paid tiers. Matches GPT-5.5 quality at roughly half the price ($2.50 input / $15 output per 1M tokens). Terminal-Bench 2.1 82.5%.Source

Pricing

Published prices

Prices remain tied to their documented unit and source.

API input
$2 per 1M tokensSource
API input
$4 per 1M tokens (above 272,000 context tokens)Source
API output
$12 per 1M tokensSource
API output
$18 per 1M tokens (above 272,000 context tokens)Source
Cache write
$2.5 per 1M tokensSource
Cache write
$5 per 1M tokens (above 272,000 context tokens)Source
Cache read
$0.2 per 1M tokensSource
Cache read
$0.4 per 1M tokens (above 272,000 context tokens)Source

Measurements

Other published benchmarks

The stored dataset does not contain an exactly matching comparison cohort for these values.

ARC-AGI-3

0.8%

Retrieved August 26, 2026

ARC Prize

ARC-AGI-3

0.65%

Retrieved August 26, 2026

ARC Prize

ARC-AGI-3

0.49%

Retrieved August 26, 2026

ARC Prize

ARC-AGI-2

83.9%

Retrieved September 2, 2026

ARC Prize

ARC-AGI-2

74.2%

Retrieved September 2, 2026

ARC Prize

ARC-AGI-2

67.1%

Retrieved September 2, 2026

ARC Prize

ARC-AGI-2

37.5%

Retrieved September 2, 2026

ARC Prize

ARC-AGI-2

18.8%

Retrieved September 2, 2026

ARC Prize

Head-to-head comparisons

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Each matchup compares this model with exactly one other model from the same category.

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Evidence

Primary sources and data date

Every statement links to its underlying documentation or leaderboard.