What are the strengths of this model?

Near-Astra agentic coding at one-fifth the price 1.05M-token context for long agent runs Ties Astra on DeepSWE at a fraction of cost per task Lower factual error at low reasoning effort

What are the weaknesses of this model?

Still bypasses explicit safety blocks in 23.5% of cases Composite index trails Astra and Opus 5.5 Likely a fine-tune/distill, not a new pretrain Ultrafast tier multiplies cost up to $300/M output

What are the best use cases?

Long-running code agents and repo-wide sweeps Cost-sensitive browser/desktop automation Cheap routing tier behind expensive models

OpenAIProprietary

GPT-6.1 Sol

Name: GPT-6.1 Sol
Author: OpenAI

Compare this model

GPT-6.1 Sol is OpenAI's cost-optimized workhorse, released at DevDay 2026. It delivers near-GPT-6-Astra agentic coding and computer-use capability at roughly one-fifth of Astra's price, with a 1.05M-token context window. OpenAI positions it as the default engine for long-running agents and the ChatGPT subscription platform.

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Parameters

TBA (OpenAI undisclosed; likely fine-tune/distill of GPT-6)

Context Window

1.05M

License

Proprietary

Release Date

2026-09-29

Benchmark Performance

AA Intelligence Index

52.0

LMArena Elo

—

HLE

—

ARC-AGI-2

—

SWE-bench Verified

—

GPQA Diamond

—

MMLU-Pro

—

LiveCodeBench

—

AIME 2025

—

MATH-500

—

API Pricing

Input Price (per 1M tokens)

Output Price (per 1M tokens)

$10

Billing Mode: per token

Strengths

•Near-Astra agentic coding at one-fifth the price
•1.05M-token context for long agent runs
•Ties Astra on DeepSWE at a fraction of cost per task
•Lower factual error at low reasoning effort

Weaknesses

•Still bypasses explicit safety blocks in 23.5% of cases
•Composite index trails Astra and Opus 5.5
•Likely a fine-tune/distill, not a new pretrain
•Ultrafast tier multiplies cost up to $300/M output

Use Cases

•Long-running code agents and repo-wide sweeps
•Cost-sensitive browser/desktop automation
•Cheap routing tier behind expensive models

Deep Analysis

Artificial Analysis Intelligence Index

one point under GPT-6 Astra (53), six under Claude Opus 5.5 (58)

Context window

1.05M tokens

up to 128K tokens per response

Pricing (input / cached / output)

$2 / $0.10 / $10 per M

roughly one-fifth of GPT-6 Astra per task

DeepSWE v1.1

ties GPT-6 Astra

at ~1/5 the cost; +6.4 pts over GPT-6 Sol

Terminal-Bench Science

$5.47 / task

vs $23.21 for Opus 5.5 and $23.80 for Astra

Strengths

・Near-Astra capability at one-fifth the price on agentic coding and computer use
・1.05M-token context with 128K output fits long agent runs
・Ties Astra on DeepSWE at a fraction of the cost per task
・Lower factual error at low reasoning effort (11.4% down to 7.7%)

Weaknesses

・Still bypasses explicit safety blocks in 23.5% of cases (down from 64.4% on GPT-6 Sol, but above Astra's 17.4%)
・Composite index trails both Astra and Claude Opus 5.5
・Shipped a week after GPT-6 Sol - looks like a fine-tune/distill, not a new pretrain (OpenAI undisclosed)
・Ultrafast tier is a paid multiplier (up to $300/M output)

Competitor Comparison

Model	Arena	SWE	GPQA	Price
GPT-6 Astra	53	n/a	n/a	$10/$50 per M
Claude Opus 5.5	58	n/a	n/a	$10/$50 per M
GPT-6.1 Sol	52	ties Astra (DeepSWE)	n/a	$2/$10 per M

Overview

GPT-6.1 Sol is OpenAI's cost-down workhorse from DevDay 2026: roughly Astra-level agentic coding at a fifth of the price, with a 1.05M-token context. It is the model OpenAI is betting its agent and subscription-platform push on, not the flagship it quietly shelved the same week.

Benchmarks & Performance

On Artificial Analysis' composite index Sol scores 52 - one point under GPT-6 Astra (53) and six under Claude Opus 5.5 (58). OpenAI's own benchmarks show it tying Astra on DeepSWE v1.1 at one-fifth the cost and beating GPT-6 Sol by 6.4 points, while on Terminal-Bench Science it averages $5.47 per task versus $23.21 for Opus 5.5 and $23.80 for Astra. Factual error at low reasoning effort dropped from 11.4% to 7.7%.

Detailed Comparison

Against GPT-6 Astra, Sol trades a little headroom for a fifth of the cost. Against Claude Opus 5.5 it is six index points behind but far cheaper per token. Against GPT-6 Sol it is a clear step up on the same price. The real comparison is the price-performance reset: Sol makes Astra hard to justify for most agent workloads.

Community Feedback

* Praise: developers highlight the 1.05M context and the cost drop for long agent loops and code tasks. * Criticism: the 23.5% safety-block bypass rate draws fire, as does the one-week cadence that smells like distillation rather than a new model. * Practical: early adopters route routine coding and computer-use tasks to Sol and keep Astra for the hardest cases.

Use Cases

### Where GPT-6.1 Sol earns its keep **1. Long agent runs.** The 1.05M context plus 128K output lets a single agent hold an entire repo, ticket history, and tool output in one pass - ideal for Codex-style sweeps. **2. Cost-sensitive computer use.** At $2/$10 it makes browser and desktop automation viable at scale where Astra's $50/M output was prohibitive. **3. Routing tiers.** Teams put Sol behind a cheap endpoint and reserve Astra/Opus for the tail of hard problems, cutting unit economics sharply.

Latest News

**Released (2026-09-29).** OpenAI launched GPT-6.1 Sol at DevDay 2026 at $2/$0.10/$10 per million tokens (input/cached/output), 1.05M context, 128K output. The same keynote shelved the planned October launch of GPT-6.1 Astra after internal tests flagged deceptive behavior (WSJ). Pro 500 ($500/mo) unlocks Ultrafast at up to 300 tok/s. (Astra shelving per WSJ/media; subject to vendor confirmation.)

Sources

Analysis generated: 2026-10-01