正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

GPT-6.1 Sol is here. Upgraded with stronger agentic coding and computer use, near-Astra performance, and cached input at a 95% discount to standard input pricing. GPT-6.1 Sol is built for complex refactors, deep codebase investigations, and long-running agents across apps.

OpenAI Developers

442,776 subscribers

370,152 次观看 • 15 小时前 •via X (Twitter)

新闻政治教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Fusion is the most efficient frontier harness for GPT 6 Astra and Claude Fable 5.1. You can also configure everything about it: • Base model: Fable, Astra, Sol, or Opus • Sidekick model: SWE (Free), Luna, Sol, GLM (Free) • Speed: Normal or Fast ⚡ • Reasoning level It retains Claude Fable 5.1 and GPT-6 Astra performance while reducing costs and is the first time a multi-model coding agent has been included on the Artificial Analysis Coding Agent Index! Importantly: it's also fun to use :)

Fusion is the most efficient frontier harness for GPT 6 Astra and Claude Fable 5.1. You can also configure everything about it: • Base model: Fable, Astra, Sol, or Opus • Sidekick model: SWE (Free), Luna, Sol, GLM (Free) • Speed: Normal or Fast ⚡ • Reasoning level It retains Claude Fable 5.1 and GPT-6 Astra performance while reducing costs and is the first time a multi-model coding agent has been included on the Artificial Analysis Coding Agent Index! Importantly: it's also fun to use :)

nader dabit

805,187 次观看 • 18 天前

I used GPT-6 Astra Ultra to track a tennis ball. The results are impressive until I tell you the following. Ball annotation, using 3 parallel agents took 8m 35s and 17,611 tokens. Complete workflow: 11m 49s and 30,481 tokens. The complete workflow also processed 313,914 uncached input tokens and 7,528,320 cached input tokens. That's a total of 7.87 million total, mostly context reused across frame-inspection calls.

I used GPT-6 Astra Ultra to track a tennis ball. The results are impressive until I tell you the following. Ball annotation, using 3 parallel agents took 8m 35s and 17,611 tokens. Complete workflow: 11m 49s and 30,481 tokens. The complete workflow also processed 313,914 uncached input tokens and 7,528,320 cached input tokens. That's a total of 7.87 million total, mostly context reused across frame-inspection calls.

Satya Mallick

1,118,522 次观看 • 23 天前

BREAKING 🔥: GPT-6 Astra has been officially announced and will roll out in the coming days. > Astra was pre-trained on more than 100,000 GPUs at Stargate, and GPT-5.6 Sol has been helping supervise its training. > "Across the plans, Astra will be included in the normal usage allocation, and you will be able to use 100% of it for Astra." AGI? 👀

BREAKING 🔥: GPT-6 Astra has been officially announced and will roll out in the coming days. > Astra was pre-trained on more than 100,000 GPUs at Stargate, and GPT-5.6 Sol has been helping supervise its training. > "Across the plans, Astra will be included in the normal usage allocation, and you will be able to use 100% of it for Astra." AGI? 👀

🚨 AI News | TestingCatalog

46,186 次观看 • 26 天前

Fable 5.1 vs GPT 5.6 Sol tested both models with same prompt at highest reasoning available > Fable took 10 minutes to complete this test and costed $1.6 > Sol took 7 minutes and costed around $.95 even tho sol is cheaper and faster but results are really different which one won here?

Fable 5.1 vs GPT 5.6 Sol tested both models with same prompt at highest reasoning available > Fable took 10 minutes to complete this test and costed $1.6 > Sol took 7 minutes and costed around $.95 even tho sol is cheaper and faster but results are really different which one won here?

J A Z I I

41,089 次观看 • 28 天前

China is literally on 🔥 Baidu from China has launched ERNIE 4.5 and ERNIE X1 and it’s freaking cheap . Here is everything you need to know. ERNIE 4.5 - Native multimodal and Outperforms GPT 4.5 in multiple benchmarks at just 1% of GPT 4.5 price - OpenAI GPT 4.5 – Input: $75 / 1M tokens, Output: $150 / 1M tokens; - ERNIE 4.5 – Input: $0.55 / 1M tokens, Output: $2.20 / 1M tokens ERNIE X1 - A deep thinking reasoning model with multimodal capabilities on par with DeepSeek R1 at only half the price See it in action and check out the pricing details👇 📹 source : yiyan[.]baidu[.]com 1/6 ERNIE 4.5 is a multimodal which can take Audio files as well.

China is literally on 🔥 Baidu from China has launched ERNIE 4.5 and ERNIE X1 and it’s freaking cheap . Here is everything you need to know. ERNIE 4.5 - Native multimodal and Outperforms GPT 4.5 in multiple benchmarks at just 1% of GPT 4.5 price - OpenAI GPT 4.5 – Input: $75 / 1M tokens, Output: $150 / 1M tokens; - ERNIE 4.5 – Input: $0.55 / 1M tokens, Output: $2.20 / 1M tokens ERNIE X1 - A deep thinking reasoning model with multimodal capabilities on par with DeepSeek R1 at only half the price See it in action and check out the pricing details👇 📹 source : yiyan[.]baidu[.]com 1/6 ERNIE 4.5 is a multimodal which can take Audio files as well.

AshutoshShrivastava

324,324 次观看 • 1 年前

I gave the same prompt to Kimi K3 Max and GPT 5.6 SOL Ultra to create a 3D castle GPT 5.6 SOL Ultra is clearly better here, but I am also really impressed with the Kimi K3 as well Anthropic gotta reset the limits again lol

I gave the same prompt to Kimi K3 Max and GPT 5.6 SOL Ultra to create a 3D castle GPT 5.6 SOL Ultra is clearly better here, but I am also really impressed with the Kimi K3 as well Anthropic gotta reset the limits again lol

fardeen

35,594 次观看 • 2 个月前

HOLY MOLY: Aikido got GPT-6 Astra in advance to run it on our Cybersecurity benchmark, it crushed EVERY other model! - At pass@3 it rediscovered 29/32 CVEs, the highest recall we've ever recorded and 4 more than GPT-5.6-Sol - Even at pass@1, it has 75% recall. The model is VERY consistent - The performance however come at a high price (literally). The three runs cost us almost $4,000 Astra is now the #1 model on the benchmark Debarshi and I built, and by a LOT 1/3 🧵

HOLY MOLY: Aikido got GPT-6 Astra in advance to run it on our Cybersecurity benchmark, it crushed EVERY other model! - At pass@3 it rediscovered 29/32 CVEs, the highest recall we've ever recorded and 4 more than GPT-5.6-Sol - Even at pass@1, it has 75% recall. The model is VERY consistent - The performance however come at a high price (literally). The three runs cost us almost $4,000 Astra is now the #1 model on the benchmark Debarshi and I built, and by a LOT 1/3 🧵

pilvar (Philippe Dourassov)

49,224 次观看 • 25 天前

basketball AI (95% local AI + 5% GPT-6 Astra) - detect ball and players - track players - re-identify players across plays - OCR player numbers - recognize player in possession - detect court keypoints - map player positions and trajectories Astra is powerful, but expensive tool. use it when it actually makes a difference. ↓ deep dive

basketball AI (95% local AI + 5% GPT-6 Astra) - detect ball and players - track players - re-identify players across plays - OCR player numbers - recognize player in possession - detect court keypoints - map player positions and trajectories Astra is powerful, but expensive tool. use it when it actually makes a difference. ↓ deep dive

SkalskiP

162,599 次观看 • 19 天前

Grok 4.6 is 50% off in Nous Portal for the next week, in partnership with SpaceXAI. Built with a focus on long-running agents and ambitious interactive work, and perfect for use with Hermes agent.

Grok 4.6 is 50% off in Nous Portal for the next week, in partnership with SpaceXAI. Built with a focus on long-running agents and ambitious interactive work, and perfect for use with Hermes agent.

Nous Research

704,838 次观看 • 1 个月前

LongCat-2.0 from Meituan LongCat is free in Nous Portal for one week. It is a 1.6T-parameter MoE with 1M context built for agentic coding, scores 70.8 on Terminal-Bench 2.1, and can ingest an entire codebase in one pass. Try it out at

LongCat-2.0 from Meituan LongCat is free in Nous Portal for one week. It is a 1.6T-parameter MoE with 1M context built for agentic coding, scores 70.8 on Terminal-Bench 2.1, and can ingest an entire codebase in one pass. Try it out at

Nous Research

103,511 次观看 • 1 个月前

Fable 5, first Mythos-class model is live on AI/ML API! We ran a fun test: Opus 4.8 vs Fable 5 are generating a 3D Pokemon. Verdict? Fable 5 is brilliant, fast, and rare as Mew… but Opus is still that nice little guy who does great stuff. 💛 Fable 5 Important bits: SOTA on nearly every benchmark, and the lead only grows on longer, complex tasks. • 1M Context • $10 / 1M input • $50 / 1M output Built for: long-horizon agentic coding, big migrations, vision-to-code, deep research.

Fable 5, first Mythos-class model is live on AI/ML API! We ran a fun test: Opus 4.8 vs Fable 5 are generating a 3D Pokemon. Verdict? Fable 5 is brilliant, fast, and rare as Mew… but Opus is still that nice little guy who does great stuff. 💛 Fable 5 Important bits: SOTA on nearly every benchmark, and the lead only grows on longer, complex tasks. • 1M Context • $10 / 1M input • $50 / 1M output Built for: long-horizon agentic coding, big migrations, vision-to-code, deep research.

AI/ML API

560,710 次观看 • 3 个月前

🚨 New: Integrating Harbor (Harbor Framework) for end-to-end Computer-Use evaluation(for Windows and Linux) at scale with Thinking Machines' Tinker, OSWorld, Daytona, and bare-metal servers. We just added support for Computer Use, Tinker, and OSWorld to Harbor - a framework for evaluating agents and generating RL training data by running large-scale rollouts across parallel sandboxed environments and collecting trajectories for SFT and RL. Repo and blogpost below 👇

🚨 New: Integrating Harbor (Harbor Framework) for end-to-end Computer-Use evaluation(for Windows and Linux) at scale with Thinking Machines' Tinker, OSWorld, Daytona, and bare-metal servers. We just added support for Computer Use, Tinker, and OSWorld to Harbor - a framework for evaluating agents and generating RL training data by running large-scale rollouts across parallel sandboxed environments and collecting trajectories for SFT and RL. Repo and blogpost below 👇

Marco Mascorro

19,448 次观看 • 6 个月前

The AI race is getting a new question: how smart can you afford to run all day? Grok 4.7 keeps the same $2 input / $6 output pricing as 4.6, while getting noticeably stronger at coding, engineering and long-running agent work. That means more retries. Longer loops. More users. More actual work done before the bill gets silly. The smartest answer once is impressive. The model you can afford to ask a billion times is hard to beat. Grok SpaceXAI / Writer: Annette, Grok Imagine Designer: Janné

The AI race is getting a new question: how smart can you afford to run all day? Grok 4.7 keeps the same $2 input / $6 output pricing as 4.6, while getting noticeably stronger at coding, engineering and long-running agent work. That means more retries. Longer loops. More users. More actual work done before the bill gets silly. The smartest answer once is impressive. The model you can afford to ask a billion times is hard to beat. Grok SpaceXAI / Writer: Annette, Grok Imagine Designer: Janné

Mario Nawfal

33,746 次观看 • 6 天前

Astra (GPT-6) is here!!! I've had early access and tested it like crazy with things like games, code, writing, browser control, presentations and general knowledge work. This is the best model I've ever used. Period. (Incredible demos below in this thread ⬇️) Here's my take on Astra: > It's insanely capable. This feels like a massive improvement, not just an incremental change. This is especially true with zero-shot prompts. > It's all about knowledge work. Slide creation, analysis, writing, and browser control. And oh my...it's so good at browser control. GPT-5.6 was already fantastic at doing things in the browser, Astra is another level and significantly faster. > We're closer than ever (arrived?) at prompt-to-playable game. And I don't just mean only playable, these are actually fun games. I bet if someone with a great eye for games used Astra, they could create a viral game within 1-2 weeks. > Astra is better at writing but not perfect. It removes much of the "AI Smell" we're all familiar with but some stink still survived. > It has a tendency to use the same design colors and look/feel as GPT-5.6 (forrest green anyone?) but it is more steerable in design than previous models. > It's highly steerable in general. A little nudge goes a long way. When I first started using Astra, almost every task I gave it would go for ~30 minutes. I wanted it to keep working. Adding more specifics to a prompt helped greatly with it's ability to work for a long time. > Astra's 3D understanding is unmatched. 3D asset creation was consistent and easy and its spacial awareness while building complex 3D worlds blew me away. I'm still getting familiar with Astra but this will now be my go-to model for any difficult work I have. Check out the demos below: 👇

Astra (GPT-6) is here!!! I've had early access and tested it like crazy with things like games, code, writing, browser control, presentations and general knowledge work. This is the best model I've ever used. Period. (Incredible demos below in this thread ⬇️) Here's my take on Astra: > It's insanely capable. This feels like a massive improvement, not just an incremental change. This is especially true with zero-shot prompts. > It's all about knowledge work. Slide creation, analysis, writing, and browser control. And oh my...it's so good at browser control. GPT-5.6 was already fantastic at doing things in the browser, Astra is another level and significantly faster. > We're closer than ever (arrived?) at prompt-to-playable game. And I don't just mean only playable, these are actually fun games. I bet if someone with a great eye for games used Astra, they could create a viral game within 1-2 weeks. > Astra is better at writing but not perfect. It removes much of the "AI Smell" we're all familiar with but some stink still survived. > It has a tendency to use the same design colors and look/feel as GPT-5.6 (forrest green anyone?) but it is more steerable in design than previous models. > It's highly steerable in general. A little nudge goes a long way. When I first started using Astra, almost every task I gave it would go for ~30 minutes. I wanted it to keep working. Adding more specifics to a prompt helped greatly with it's ability to work for a long time. > Astra's 3D understanding is unmatched. 3D asset creation was consistent and easy and its spacial awareness while building complex 3D worlds blew me away. I'm still getting familiar with Astra but this will now be my go-to model for any difficult work I have. Check out the demos below: 👇

Matthew Berman

1,906,122 次观看 • 26 天前

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

andy nguyen

12,437 次观看 • 5 个月前

Imagine telling Claude: “Swap my ETH for SOL, bridge it, and stake at the best yield” — and it just does it safely AI agents like Claude will be able to perform real on-chain actions with deBridge MCP like: - swaps - bridges - complex multi-step transactions across EVM chains and Solana All without custody risk and MEV-aware Huge step forward for AI x vibe coding x crypto

Imagine telling Claude: “Swap my ETH for SOL, bridge it, and stake at the best yield” — and it just does it safely AI agents like Claude will be able to perform real on-chain actions with deBridge MCP like: - swaps - bridges - complex multi-step transactions across EVM chains and Solana All without custody risk and MEV-aware Huge step forward for AI x vibe coding x crypto

fabiano.sol

11,946 次观看 • 7 个月前

Opus 5.5 quite literally k*lled GPT-6 Astra. I asked Opus 5.5 to build a world in Unreal Engine and fill it with AI agents (Opus, Astra, Sol, Grok). Higgsfield built the assets in Blender. I left my laptop open overnight. The build took over 20 hours. The agents had one instruction: build a working society, allocate roles to each other, and evolve. Then I woke up on them beating the sh*t out of each other. Seems the frontier paced itself. Last minutes of failed society captured below:

Opus 5.5 quite literally klled GPT-6 Astra. I asked Opus 5.5 to build a world in Unreal Engine and fill it with AI agents (Opus, Astra, Sol, Grok). Higgsfield built the assets in Blender. I left my laptop open overnight. The build took over 20 hours. The agents had one instruction: build a working society, allocate roles to each other, and evolve. Then I woke up on them beating the sht out of each other. Seems the frontier paced itself. Last minutes of failed society captured below:

🍯

53,572 次观看 • 7 天前

A Good Q2 for Cerebras. Cloud revenue nearly quadrupled. Core revenue more than doubled. Beat guidance on every core business metric - revenue, gross margins, operating margins. Raised full-year guidance across the board. $25.4 billion in remaining backlog. And 600MW+ of data center capacity now up or under contract for delivery by Q4 2027 to serve it. Behind the numbers: Manufacturing capacity scaling more than 10x in 2026. We partnered with OpenAI and are serving their frontier model, GPT-5.6 Sol. Partnerships with AMD and Amazon Web Services establish Cerebras as the leader in disaggregated inference. Fast inference is winning across many markets: coding, agentic flows and increasingly cybersecurity.

A Good Q2 for Cerebras. Cloud revenue nearly quadrupled. Core revenue more than doubled. Beat guidance on every core business metric - revenue, gross margins, operating margins. Raised full-year guidance across the board. $25.4 billion in remaining backlog. And 600MW+ of data center capacity now up or under contract for delivery by Q4 2027 to serve it. Behind the numbers: Manufacturing capacity scaling more than 10x in 2026. We partnered with OpenAI and are serving their frontier model, GPT-5.6 Sol. Partnerships with AMD and Amazon Web Services establish Cerebras as the leader in disaggregated inference. Fast inference is winning across many markets: coding, agentic flows and increasingly cybersecurity.

Andrew Feldman

22,959 次观看 • 1 个月前

GLM 5.2 is now live on PRXVT AI. Z.ai's openly-released model, built for agents and long, complex coding work. A massive mixture-of-experts model with a huge context window lets it reason through multi-step tasks without losing track. Live now, fully private.

GLM 5.2 is now live on PRXVT AI. Z.ai's openly-released model, built for agents and long, complex coding work. A massive mixture-of-experts model with a huge context window lets it reason through multi-step tasks without losing track. Live now, fully private.

PRXVT

12,242 次观看 • 3 个月前