Rishabh Srivastava retweeted
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, grade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
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Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, grade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
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Rishabh Srivastava retweeted
opus 5.5 with our @tryfactiq plugin creating video explainers for big news 🙏
Insane creative skills in this model (this is js only!!)
Financial Times · 14 Oct 2026 · BofA profits drop 17% after $1.2bn money laundering fine
Insane creative skills in this model (this is js only!!)
Financial Times · 14 Oct 2026 · BofA profits drop 17% after $1.2bn money laundering fine
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Sheesh realtime LLMs in voice mode remind me of first dates while single
You see someone intriguing, she seems full of potential, initially sounds very interesting because she’s socially great. But the moment you talk about anything substantial - you realize it's just hot air and vapidness wrapped up in a shiny veneer
LLMs without thinking tokens are still very, very mid 😅
You see someone intriguing, she seems full of potential, initially sounds very interesting because she’s socially great. But the moment you talk about anything substantial - you realize it's just hot air and vapidness wrapped up in a shiny veneer
LLMs without thinking tokens are still very, very mid 😅
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Rishabh Srivastava retweeted
GPT-6.1-Sol’s release today nicely shifted the intelligence-vs-cost frontier.
If you’re using GPT and care about intelligence per dollar, GPT-6.1-Sol deserves a look.
If you want the highest intelligence score regardless of cost, Opus 5.5 still leads.
If you’re using GPT and care about intelligence per dollar, GPT-6.1-Sol deserves a look.
If you want the highest intelligence score regardless of cost, Opus 5.5 still leads.
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Goodbye, subsidised consumer plans. You were great while you lasted 🫡
Hi,
Tomorrow we are re-opening the Pro $200 subscriptions to new subscribers, but together with it we are also changing how we calculate the usage for it. In effect, if you do the math, it will net out at half the dollar in API spend compared to the old Pro $200 plan.
Now that it's said, let me explain why this is happening and why you will still get more work done than if you were on the Pro $200 subscription one month ago.
(a) We didn't want to compromise in other ways and are committing to not reintroducing the 5h limit, so that you can fully use the weekly usage when you want.
(b) On the subscription, we guarantee that over time you always get more work done and with an increasing level of quality. This means that you will continue to get more value per dollar spent as a result of models getting more efficient and us passing down the improvements in the form of API price reductions.
(c) We don't want to put an incentive on ourselves to artificially inflate the API list prices to make it look like you are getting a lot (and workaround it through discounts, etc). Instead we want to continue to both rapidly reduce prices and increase capabilities of models on the API. This week we introduced GPT-6 Sol and GPT-6 Luna at 50% of their previous price. Over time, we see prices go low enough that it makes sense for most to buy usage as needed without there being a significant gap between what you get in a subscription and what you get in the API for a dollar spent.
(d) Tomorrow, we are adding more things to the subscription that won't draw on the usage, I won't reveal what that is yet.
I wanted to be transparent before all the big announcements tomorrow. Lots of new exciting things are coming to the subscriptions that will make it super compelling, but I wanted to make sure to share this change ahead of time so you can all understand it before we shower you with good news.
Codexingly,
Tibo
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jfc sonnet 5.5 is _fast_
prompt to PR in ~20 seconds for a simple task (update internal library to add sonnet 5.5 support). wtf
prompt to PR in ~20 seconds for a simple task (update internal library to add sonnet 5.5 support). wtf
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holy shit opus 5.5 just one shotted this video about Nvidia stock buybacks
data was from the factiq plugin, everything else was a single opus prompt with Claude code
weirdly, the less constraints we gave the model, the better was its output
data was from the factiq plugin, everything else was a single opus prompt with Claude code
weirdly, the less constraints we gave the model, the better was its output
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this was another one about china and us trade. kinda nuts that this is all just one shotted. wtf
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fascinating to see people on claude/chatgpt enterprise plans
mid-level managers/ics seem much less likely to experiment - because it counts against a finite usage quota + they're worried about their usage being thought of as "trivial"
approach seems to be "to start, i need to find an experiment that'll be perceived of valuable". not "let's just take this thing for a ride and see what it can do"
folks that pay for their own max plans have such a massive advantage - they use agents much more (thanks to the subscription subsidy), and naturally have more intuition about how to get the best from them
mid-level managers/ics seem much less likely to experiment - because it counts against a finite usage quota + they're worried about their usage being thought of as "trivial"
approach seems to be "to start, i need to find an experiment that'll be perceived of valuable". not "let's just take this thing for a ride and see what it can do"
folks that pay for their own max plans have such a massive advantage - they use agents much more (thanks to the subscription subsidy), and naturally have more intuition about how to get the best from them
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Rishabh Srivastava retweeted
People forget how bad Claude used to be.
In YC W23 we got access through a Slack bot, and it was generally considered a joke next to ChatGPT, which was all anyone in the world was talking about. Copilot was SotA for real engineering work.
SVB collapsed the day before fundraising. Cursor wasn't a thing yet. Claude Code wouldn't come out for 2 more years (!). Prompt engineering was the hot skill to double down on.
Founders who built tightly coupled harnesses and guardrails had a bad time once agents actually worked in late 2025.
That was only ~3 years ago. Things are changing mind-bendingly fast.
In YC W23 we got access through a Slack bot, and it was generally considered a joke next to ChatGPT, which was all anyone in the world was talking about. Copilot was SotA for real engineering work.
SVB collapsed the day before fundraising. Cursor wasn't a thing yet. Claude Code wouldn't come out for 2 more years (!). Prompt engineering was the hot skill to double down on.
Founders who built tightly coupled harnesses and guardrails had a bad time once agents actually worked in late 2025.
That was only ~3 years ago. Things are changing mind-bendingly fast.
i remember 5 years ago, when anthropic was a slack bot and we were part of their beta
they fucked up their launch timeline
and chat beat them
and i thought: it's over for them
5 years later, they're head to head
facebook / meta had some terrible flops, but they just launched muse, which everyone loves
the biggest companies in the world don't just wake up and magically discover pmf
they find pmf by stacking learning over learning and launching and relaunching
most importantly, they don't give up. not giving up is the most important compounding advantage
everyone can become someone's competition on a long enough time horizon
yes, no one can rival XYZ company in 3 months
but give it 5 years - impossible things become possible on the path from 3 months -> 5 years
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we're at the part of the cycle where i'm saying this to LLMs 🫠
> i don't get exactly what you changed. i'm very sleepy rn and my organic brain is slow. please be patient and explain again
> i don't get exactly what you changed. i'm very sleepy rn and my organic brain is slow. please be patient and explain again
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what a day for ai users! super excited for luna in particular. half the cost and better intelligence make it the best (by far - including chinese oss models) for data processing
badass show of strength by american frontier labs today!
badass show of strength by american frontier labs today!
Introducing GPT-6 Sol and Luna, bringing the advances behind Astra to faster, more affordable models. ✨
💻 Stronger coding and computer use
🎯 Improved factuality and alignment
💬 Clearer answers with less jargon
> On AutomationBench, Sol at xhigh effort outperforms Claude Opust 9% of its cost per task.
> On OSWorld 2.0 offline, Luna at max effort exceeds GPT-5.6 Sol at medium effort at one-tenth the cost.
> Sol makes about half as many mistakes as GPT-5.6 Sol on our internal factuality evaluation of conversations where users previously flagged errors.
> Improved prompt caching helps agents reuse more context, with 90% discounts on cached input-token reads. Developers can change reasoning effort and tool availability without breaking cache.
Rolling out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise and Edu users, and available in the OpenAI API. Free and Go users can access Luna in the desktop app. These models are not yet available in Chat.
API pricing per 1M tokens:
Sol: $2 input / $10 output
Luna: $0.10 input / $0.50 output
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as an example, it's found 7 bugs in US-listed company's SEC filings so far
as just one example - Comfort Systems ($FIX) filed a Q1 2026 10-Q with an XBRL error - tagging Q1 2025 revenue ($1.83B) as full-year 2025
super impressed with this god-mode opus
as just one example - Comfort Systems ($FIX) filed a Q1 2026 10-Q with an XBRL error - tagging Q1 2025 revenue ($1.83B) as full-year 2025
super impressed with this god-mode opus
what the flying fuck opus 5.5 is fantastic
blazing fast, token efficient, pays a lot of attention to detail, and has already found issues in our pipeline that fable and astra missed
excited to see these models improve so quickly, and to see what oai has in store today!
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what the flying fuck opus 5.5 is fantastic
blazing fast, token efficient, pays a lot of attention to detail, and has already found issues in our pipeline that fable and astra missed
excited to see these models improve so quickly, and to see what oai has in store today!
blazing fast, token efficient, pays a lot of attention to detail, and has already found issues in our pipeline that fable and astra missed
excited to see these models improve so quickly, and to see what oai has in store today!
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Hurray! Hope ChatGPT does this too. Super annoying for non technical users to know when to use chat and when to use work
My 60+ yr old dad asked trivial questions on work mode, and ended up blowing past his monthly quota in 3 days
My 60+ yr old dad asked trivial questions on work mode, and ended up blowing past his monthly quota in 3 days
Claude Cowork and chat are merging into one Claude.
Ask a quick question or hand over a report, and Claude takes it from there, even after you close your laptop. If something's unclear, Claude asks—you keep the final say.
Rolling out to Pro and Max over the next few weeks.
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ran deepseek 4.1 flash on a few private evals!
- ~60% fewer thinking tokens compared to previous iteration -> leads to much better e2e latency and much lower costs
- e2e cost per task now roughly similar to pre-price-hike deepseek v4 flash, despite per-token costs being higher
- *very* substantial improvement over v4 flash
- will almost certainly establish a new pareto frontier for cost/perf
if you don't need the extra intelligence and your tasks are not very agentic-loop heavy (where deepseek's cheap cache shines through) gpt-5.6-luna is still the best option (25% cheaper per task in my evals, ~15% faster e2e)
for everything else (sp code), deepseek is a great alternative
- ~60% fewer thinking tokens compared to previous iteration -> leads to much better e2e latency and much lower costs
- e2e cost per task now roughly similar to pre-price-hike deepseek v4 flash, despite per-token costs being higher
- *very* substantial improvement over v4 flash
- will almost certainly establish a new pareto frontier for cost/perf
if you don't need the extra intelligence and your tasks are not very agentic-loop heavy (where deepseek's cheap cache shines through) gpt-5.6-luna is still the best option (25% cheaper per task in my evals, ~15% faster e2e)
for everything else (sp code), deepseek is a great alternative
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Wow. Cheaper than luna (atleast on a per token basis), with perf between terra and sol
Thank you deepseek - the openness with which they’re sharing their IP is incredible! Amazing to see the price-performance frontier improve so rapidly
Thank you deepseek - the openness with which they’re sharing their IP is incredible! Amazing to see the price-performance frontier improve so rapidly
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient.
🔹 Introducing the smallest model in our new architecture family, with native visual understanding.
🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models.
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