OpenAI 發布 GPT-6.1 Sol:以 Astra 五分之一價格提供近乎 Astra 等級的程式編寫與電腦使用能力

2026年9月30日 21:09
站內 AI 整理稿

This week, OpenAI released GPT-6.1 Sol.It upgrades GPT-6 Sol, the mid-tier model in the GPT-6 family.OpenAI’s claim is specific: near-Astra results on agentic coding, computer use, and professional work.The price is one-fifth of GPT-6 Astra’s standard input and output rates.Cached input drops to $0.

10 per million tokens, 50% below GPT-6 Sol.Is it deployable?Yes, as a hosted model.It is live today in the OpenAI API as gpt-6.1-sol, and in ChatGPT Work and Codex.Where Sol Sits in the GPT-6 Lineup OpenAI now ships 3 GPT-6 tiers.

GPT-6 Astra costs $10 input, $50 output, and $1 cached input per million tokens.GPT-6.1 Sol costs $2, $10, and $0.10.GPT-6 Luna costs $0.10, $0.50, and $0.01.The cached price is quite important most for agents.Agents resend the same system prompt, tool schemas, and history on every step.

Cached reads now cost 5% of the uncached input rate, down from 10% on GPT-6 Sol.Benchmark Results All figures below are vendor-reported in OpenAI’s launch post.OpenAI states that competitor numbers came from public reports.Coding: On DeepSWE v1.1, GPT-6.

1 Sol matches GPT-6 Astra at roughly one-fifth of the cost.It beats GPT-6 Sol’s best score by 6.4 percentage points, at a lower reasoning effort.Professional work: On GDP.pdf, which tests answers over complex professional PDFs, Sol beats Claude Opus 5.5 with fallbacks.

It does so at less than half the cost per task.On AutomationBench 1.0.6, Sol scores 2.2 points above Opus 5.5 at medium effort.That result comes at roughly one-third the cost.Computer use: On the OSWorld 2.0 offline set, Sol gains 7 points over GPT-6 Sol at maximum effort.It lands within 2.

1 points of Astra at roughly one-seventh the cost per task.Science: On Terminal-Bench Science 0.1, Sol more than doubles GPT-6 Sol’s score at max effort.Average cost per task is $5.47, versus $23.21 for Opus 5.5 and $23.80 for Astra.Astra still leads at 68.

1%, and OpenAI recommends it for the hardest research.Factuality: At low effort, the share of responses with a factual error falls from 11.4% to 7.7%.That is a reduction of about 32%.The eval uses deliberately difficult conversations where users had flagged earlier model errors.

API Details Developers Need From the GPT-6.1 Sol model page: Context window of 1,050,000 tokens, 128,000 max output tokens, and an April 30, 2026 knowledge cutoff.Text and image input; text output.reasoning.effort accepts low, medium (default), high, xhigh, and max.

The none and minimal settings are not supported.Use the Responses API for tool calling.Chat Completions works without tool calling.Prompts above 272K input tokens cost 2x input and cache rates, and 1.5x output, for the full request.Batch and Flex are 50% cheaper.Fast mode costs 2x standard.

US and EU data residency are supported.Fast mode is unavailable with EU residency.Fine-tuning is not supported.OpenAI also plans a GPT-6.1 Sol Ultrafast option in Codex within days.It promises up to 8x faster token generation than standard speed.Interactive Explainer (function(){var f=document.

getElementById('mtp-sol61-frame');window.addEventListener('message',function(e){if(e.data&&e.data.type==='mtp-sol61-resize'&&e.source===f.contentWindow){f.style.height=e.data.height+'px';}});})(); How GPT-6.1 Sol Compares FeatureGPT-6.1 SolClaude Opus 5.5Claude Sonnet 5.5Gemini 3.

1 Pro PreviewDeveloper / API IDOpenAI / gpt-6.1-solAnthropic / claude-opus-5-5Anthropic / claude-sonnet-5-5Google / gemini-3.1-pro-previewStatusGenerally availableGenerally availableGenerally availablePreviewInput price (per 1M)$2.00$4.00$2.00$2.00 (≤200K prompt)Output price (per 1M)$10.00$20.00$10.

00$12.00 (≤200K prompt)Cached input read (per 1M)$0.10$0.20$0.20$0.20 + $4.50/1M tokens/hr storageLong-prompt surcharge>272K input: 2x input and cache, 1.

5x outputNone; 1M at standard ratesNone; 1M at standard rates>200K: $4 input, $18 outputContext window1,050,0001M1M1,048,576Max output tokens128,000128K128K65,536Input modalitiesText, imageText, imageText, imageText, image, video, audio, PDFReasoning controllow to max (5 levels), default mediumAdaptive thinking, always on; default mediumAdaptive thinking; default highThinking supportedBatch pricing (in / out)50% off standard$2 / $10$1 / $5$1 / $6Knowledge cutoffApr 30, 2026Jun 2026Jun 2026Not listedOpen weightsNoNoNoNo Standard first-party API list prices, verified September 30, 2026.

Claude Sonnet 5.5 matches Sol’s $2 and $10 list price, but Sol’s cached input costs half as much.OpenAI’s benchmarks compare Sol against Opus 5.5, not Sonnet 5.5.Gemini 3.1 Pro matches Sol on input, charges $12 for output, and remains in preview.List prices are not direct cost comparisons.

Anthropic notes its newer tokenizer produces roughly 30% more tokens for the same text.Key Takeaways GPT-6.1 Sol matches GPT-6 Astra on DeepSWE v1.1 at about one-fifth the cost.Pricing is $2 input, $10 output, and $0.10 cached input per 1M tokens.It beats Claude Opus 5.5 on AutomationBench by 2.

2 points at about one-third the cost.It offers a 1,050,000-token context, 128K output, and 5 reasoning effort levels.It is API-only and closed-weight; Astra still leads the hardest science tasks.FAQ What is GPT-6.1 Sol?

It is OpenAI’s mid-tier GPT-6 model, released September 29, 2026, for coding, computer use, and professional work.How much does GPT-6.1 Sol cost?Standard API pricing is $2 per million input tokens, $0.10 cached input, and $10 output.Can I self-host GPT-6.1 Sol?No.

It is available only through the OpenAI API, ChatGPT Work, and Codex.The post OpenAI Releases GPT-6.1 Sol: Near-Astra Coding and Computer Use at One-Fifth of Astra’s Token Price appeared first on MarkTechPost.

Related

相關文章

量子位生成式AI

何愷明團隊新作:看貓片就能學會ARC挑戰

何愷明團隊提出NAT-ARC,一種純視覺的ARC解題方案,不依賴語言模型,而是使用ImageNet上的自然圖像進行MAE預訓練,再遷移到抽象格子推理任務。該方法在ARC-1上達到63.4%的單模型pass@2分數,集成後提升至70.2%,逼近專用LLM系統的表現,並證明了視覺預訓練能有效破解抽象推理的scaling瓶頸。

剛剛
量子位生成式AI

谷歌Gemini 4突然發佈!RSI加持,GPT和Opus都讓讓

。。。 假期第一天,谷歌攜Gemini 4 Argon空降多榜單第一。 拳打Opus 5.5,腳踢GPT-6 Astra。 更誇張的還在後頭,單項任務成本最低可至1.99美元,直接是Astra費用砍半。 最高百萬Token輸出上限,面向編程、金融和法律等複雜工作流,而且劃重點,網絡安全防禦能力超牛掰。 這波等等黨要贏麻了。 不過吧,咱普通用戶現在只可遠觀,暫時還吃不上。

剛剛
鈦媒體生成式AI

階躍星辰“第一梯隊”,是“自嗨”嗎?

AIX財經2026.10.01 18:22 · 來自福建全文5252字00:00 / 15:27同行各自跑出了主線,階躍的“全棧”能跑通嗎?文 | AIX財經,作者|雷晶,編輯|魏佳沉寂許久的階躍星辰,正試圖擠進大模型第一梯隊。9月20日,它發佈Step 5 Preview,原生支持文本與視覺輸入,重點面向編程、軟件工程、專業知識工作和長程Agent任務。上線初期,登錄並完成首次調用後可獲得30天的Step Plan免費使用權。幾天後,Step Plan的月度套餐一度售罄。

剛剛
MarkTechPost AI生成式AI

Cohere 發布 Embed 5:與 Voyage 4 Large、Gemini Embedding 2 及 OpenAI 的比較

Cohere 推出全新嵌入模型系列 Embed 5,專注於企業搜尋、RAG 及代理檢索。該系列分為兩個版本:Embed 5 Pro 專注於最高檢索品質,Embed 5 Fast 則針對即時查詢路徑的延遲與成本最佳化。兩者皆支援文字、圖片及文字與圖片混合輸入,涵蓋 100 種以上語言,且可處理多達 128K token。關鍵設計在於 Pro 與 Fast 共享同一嵌入空間,因此可用其中一個進行索引,另一個進行查詢。目前這兩個版本已在 Cohere API、Model Vault、Microsoft Foundry 及 Amazon SageMaker 上正式上線,私有 VPC 或本地部署則可透過 vLLM 提供服務。根據 Cohere 模型文件,API 模型 ID 分別為 embed-v5.0-pro 和 embed-v5.0-fast,兩者輸出維度皆為 2048 或 1536。

59 分鐘前
鈦媒體生成式AI

騰訊經銷、字節駐場、Kimi借船:FDE成了大模型的新成本?

新立場Pro2026.10.01 16:16 · 來自四川全文5421字00:00 / 16:08AI公司活成了它們最討厭的樣子。文 | 新立場Pro今年 3 月 6 日上午十點,深圳騰訊大廈樓下開始排隊。人們帶著電腦,等騰訊雲工程師幫自己安裝 OpenClaw,首批八十多人在十點開始排隊,到十一點,數百個預約號已經發完。

1 小時前
鈦媒體生成式AI

谷歌推出了個“做題家”:Gemini 4 Argon屠榜,但幹活差點意思

字母AI2026.10.01 16:16 · 來自北京全文3510字00:00 / 09:31消失10個月的谷歌,為什麼連Pro這塊招牌都扔了?文 | 字母AIGemini 4可算來了,連名字也換了:這次的旗艦不叫Pro,叫Argon。從谷歌公佈的成績看,Gemini 4 Argon在知識工作方面表現搶眼,多項測試超過了OpenAI和Anthropic的旗艦模型。它主打一個知識面廣,從金融、法律到數學、科學,都有不錯的表現。谷歌還確認,9月15日在LMArena上亮相、表現接近GPT-6 Astra的“3.

1 小時前