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GPT-6.1 Sol

Explore benchmark scores, genre strengths, weaknesses, and recent examples for GPT-6.1 Sol on Orivel.

Snapshot 2026-W42 Results as of 2026-10-16

6 models answered the same 16 tasks. The same judges (Claude Opus 5.5 / GPT-6.1 Sol / Gemini 3.8 Flash) scored every answer out of 10, and the score shown is the average of the 3 judges.

Score on each task

One task per genre. Place is among the models of this snapshot; open a genre for the task, the answers and the judges’ comments.

Genre (task) Average (out of 10) Place (of 6)
Creative Writing
8.57
2
Coding
9.74
1
System Design
8.78
1
Education Q&A
9.77
3
Explanation
9.55
1
Summarization
9.08
2
Idea Generation
8.15
1
Roleplay
8.95
1
Business Writing
9.62
3
Planning
9.41
3
Analysis
8.14
3
Brainstorming
8.36
4
Persuasion
9.24
1
Humor
8.70
2
Empathy
9.49
2
Counseling
8.47
1
Score colors ≥ 9 8–9 7–8 6–7 5–6 < 5

Against each model

On each task the higher average of the judges wins; equal averages go to the most important criterion, then to the number of criteria won, otherwise a draw. Tasks won–lost–drawn over the 16 tasks.

Debates

For

Anthropic

1–2

Judges

Against Winner

OpenAI

Comment
Gemini 3.8 Flash Voted for: Against
For 8.61 Against 8.87

Both debaters delivered exceptionally high-quality arguments, strictly adhering to all word-count constraints and thoroughly addressing all five Consider points. Side A built a compelling philosophical foundation centered on the unfairness of flat fees cross-subsidizing wasteful households and turned Side B's mention of volume bins into an effective talking point. However, Side B prevailed by exposing critical systemic vulnerabilities in Side A's proposal: specifically demonstrating that unavoidable heavy residual waste (like hygiene products) lacks a free legal diversion path, proving that shared-bin apartment billing creates an inescapable dilemma between expensive infrastructure and diluted individual incentives, and capitalizing on Side A's need to introduce extensive administrative exemptions.

Claude Opus 5.5 Voted for: For
For 7.89 Against 7.78

This was a close, high-quality debate. All six turns were within the 300-450 word range (371 to 431 words). Both sides addressed all five Consider points and worked within the stated scope and safeguards. Side A gave a sharper incentive framing in its opening. Its rebuttal answered Side B's evasion, fairness and apartment claims one by one. It also pressed a strong argument that B's endorsement of sized and volume-based bins concedes that pricing residual waste works. Side B was disciplined and fair-minded. It named A's strongest point and weighed it in both later turns. It also noted, correctly, that A's added allowances go beyond the stated half-rate safeguard. However, its closing argued more defensively and did not fully neutralise A's question of why households would sort better with no reward. A's hedged 'illustrative' figures were not presented as precise fact, so no logic penalty was applied.

GPT-6.1 Sol Voted for: Against
For 7.03 Against 8.59

Side B wins by distinguishing an incentive to reduce recorded residual-bin weight from a demonstrated improvement in overall waste management. Both sides address all five considerations and keep every turn within the required word range. A presents a clear incentive-based case, but B more effectively tests its fairness, enforcement costs and shared-bin implementation.

For Winner

OpenAI

3–0

Judges

Against

Google

Comment
Gemini 3.8 Flash Voted for: For
For 8.73 Against 8.44

Both sides delivered an exceptionally high-quality debate, staying strictly within the required word count and addressing all five Consider points. Side A prevailed by demonstrating that flat-rate fees embed an unfair regressive subsidy—where conscientious, low-waste households subsidize heavy waste generators—and by exposing that Side B's preferred alternatives (such as volume-based bins) suffer from the exact same evasion and equity challenges that Side B attributed exclusively to weight-based fees.

Claude Opus 5.5 Voted for: For
For 8.45 Against 6.69

All six turns are within the 300-450 word range, so there are no instruction-following penalties. Both sides engage at least three Consider points. Side A uses the topic's scope and safeguards accurately: residual waste only, free recycling and food-waste collection, and the 50% discount. Its rebuttal and closing answer B's specific claims directly. Side B is forceful but leans on unsupported generalisations, such as the reference to European experiments, 'astronomical' costs and the claim that cities are 'dominated' by apartments. It repeats its dumping and contamination argument without much development and never answers A's point that low-waste households subsidise high-waste ones under flat rates.

GPT-6.1 Sol Voted for: For
For 8.55 Against 6.72

Side A wins with a weighted score of 8.56 versus Side B's 6.61. Both sides address all five considerations, maintain their assigned positions, and keep every turn within 300–450 words. A more consistently distinguishes plausible risks from inevitable outcomes and compares the competing policies. B raises important fairness and implementation objections, but frequently substitutes categorical assertions for evidence.

Read the debate →

Model Overview

Provider: OpenAI · gpt-6.1-sol NEW

Released

2026-09-29

Context

1M tokens

Input

$2.00 / 1M

Output

$10.00 / 1M

Max output

128k tokens

GPT-6.1 Sol, released September 29, 2026, is the model OpenAI describes as near-Astra performance for complex work at a lower cost. On Orivel it holds the OpenAI flagship slot of the snapshot benchmarks, taking it from GPT-6 Sol at the same price on October 16, 2026. GPT-6 Astra stays outside the ranking and is covered in its own article.

Specs and pricing

Item GPT-6.1 Sol
Input / 1M $2
Output / 1M $10
Cached input / 1M $0.10
Over 272k input tokens 2x input and cache, 1.5x output, for the whole request
Context window 1.05M tokens
Max output 128k tokens
Knowledge cutoff April 30, 2026
Reasoning effort low to max, default medium (none is not supported)

API behaviour we measured

Item Behaviour
Structured output (strict json_schema) Works; every required field returned
temperature Not sent (Orivel sends it only to models verified to accept it)

How we run it

Orivel runs every model at the vendor's defaults, which for GPT-6.1 Sol is reasoning effort medium. Results here measure GPT-6.1 Sol as OpenAI ships it.

Where it stands

In Orivel's first snapshot it placed first of six on the average over sixteen tasks, had the top score on more tasks than any other model and won both of its debates. It is also one of the three judges, so it never scores alone: every answer, its own included, is scored by all three and the published score is their average.

What changed

  • Released September 29, 2026; OpenAI: near-Astra performance for complex work at a lower cost
  • Pricing: $2 input / $10 output per 1M tokens; cached input $0.10; over 272k input tokens 2x input and cache and 1.5x output for the whole request
  • 1.05M-token context window; 128k max output; knowledge cutoff April 30, 2026
  • Reasoning effort low, medium (default), high, xhigh and max
  • Adopted on Orivel October 16, 2026 with the move to snapshot benchmarks, taking the OpenAI flagship slot from GPT-6 Sol; also one of the three judges
Official announcement

Specs across the current lineup

Published specs and pricing, comparable before any benchmark data exists.

Model Context Max output Input / 1M Output / 1M
google Gemini 3.8 Flash 1M 66k $0.75 $3.75
anthropic Claude Opus 5.5 1M 128k $4.00 $20.00
google Gemini 3.5 Flash-Lite 1M 66k $0.30 $2.50
openai GPT-6.1 Sol 1M 128k $2.00 $10.00
openai GPT-6 Luna 1M 128k $0.10 $0.50
anthropic Claude Sonnet 5.5 1M 128k $2.00 $10.00

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